• Journal of the Korean Society for information Management
• /
• v.36 no.3
• /
• pp.203-228
• /
• 2019

This study developed KISTI CLCM, a curation model suitable for the content life cycle, focusing on the KISTI Content Curation Center. For developing the KISTI Curation Model, the previously developed models DCC, DCC&U, UC3 and DCN models were reviewed and the advantages of the models connected to the mission and tasks of the digital curation center were derived. Interviews with staffs of the KISTI Content Curation Center identified the characteristics of the content and identified the level of achievement of the current task. In addition, this study proposed to enhance usability by developing KISTI content curation waves based on the UC3 model to discover user-centered services and add new values to digital resources.

• Journal of Biosystems Engineering
• /
• v.11 no.1
• /
• pp.52-63
• /
• 1986

This study was performed to find out drying characteristics and develop drying model for the design of an efficient dryer or drying system of red peper. The basic model which describes drying phenomenon of red pepper was firstly established, and drying tests were conducted at 14-different drying conditions. In this test, the effects of drying air temperature and relative humidity on the rate of drying were undertaken. Finally, a new drying model based on these experimental results was developed to describe the drying characteristics of red pepper. The results from this study may be summarized as follows. 1. Drying constant of the basic model established from Lewis' experimental model and diffusion equation was theoretically deduced as a function of moisture content and inner-temperature of red pepper. 2. From the results of drying tests, drying air temperature was found to have the greatest effect on the rate of drying. However, the effect of temperature was small for the condition of high relative humidity, and for low temperature, the effect of relative humidity was found to be large even though the range of relative humidity was low. 3. Modified Henderson equation was found to be better than Chung equation as the EMC model for the estimation of the equilibrium moisture content of red Pepper. 4. Constant-rate drying period did not exist in the red pepper drying test. And falling-rate drying period was divided into three distinct phases. Drying rate was dependent on the moisture content, the inner-temperature of red pepper and the change of physical property due to drying. 5. Drying constant increased with decrease of free moisture content, but it decreased at the end of the drying period. Also, drying constant was dependent on the drying air temperature and relative humidity. 6. The new drying model developed in this study was found to be most suitable in describing the drying characteristics of red pepper. Therefore, it may be concluded that drying time could be accurately estimated by the new drying model.

• ETRI Journal
• /
• v.30 no.6
• /
• pp.865-867
• /
• 2008

A conventional environment adaptation for robust speech recognition is usually conducted using transform-based techniques. Here, we present a discriminative adaptation strategy based on a multi-condition-trained model, and propose a new method to provide universal application to a new environment using the environment's specific conditions. Experimental results show that a speech recognition system adapted using the proposed method works successfully for other conditions as well as for those of the new environment.

• Journal of Biosystems Engineering
• /
• v.16 no.1
• /
• pp.49-59
• /
• 1991

A numerical model was developed to predict grain temperature, moisture content, and drymatter loss of rough rice in a grain storage bin. This model simulated conduction, natural convection, and mass transfer occuring inside a storage bin. The results obtained from the study were as follows. 1. The predicticted results agreed well with the measured results. 2. Rough rice could be store safely for one year in Suweon, Dajeon, and Jingu area. 3. Aeration of 5-day was required to control grain temperature and moisture content rise early in Jun and July, respectively.

• Journal of Information Processing Systems
• /
• v.11 no.2
• /
• pp.280-294
• /
• 2015

This paper presents the infectious watermarking model (IWM) for the protection of video contents that are based on biological virus modeling by the infectious route and procedure. Our infectious watermarking is designed as a new paradigm protection for video contents, regarding the hidden watermark for video protection as an infectious virus, video content as host, and codec as contagion medium. We used pathogen, mutant, and contagion as the infectious watermark and defined the techniques of infectious watermark generation and authentication, kernel-based infectious watermarking, and content-based infectious watermarking. We experimented with our watermarking model by using existing watermarking methods as kernel-based infectious watermarking and content-based infectious watermarking medium, and verified the practical applications of our model based on these experiments.

• Computers and Concrete
• /
• v.5 no.1
• /
• pp.21-36
• /
• 2008

Steel fiber reinforced concrete is increasingly used day by day in various structural applications. An extensive experimentation was carried out with w/cm ratio ranging from 0.25 to 0.40, and fiber content ranging from zero to1.5 percent by volume with an aspect ratio of 80 and silica fume replacement at 5%, 10% and 15%. The influence of steel fiber content in terms of fiber reinforcing index on the compressive strength of high-performance fiber reinforced concrete (HPFRC) with strength ranging from 45 85 MPa is presented. Based on the test results, equations are proposed using statistical methods to predict 28-day strength of HPFRC effecting the fiber addition in terms of fiber reinforcing index. A strength model proposed by modifying the mix design procedure, can utilize the optimum water content and efficiency factor of pozzolan. To examine the validity of the proposed strength model, the experimental results were compared with the values predicted by the model and the absolute variation obtained was within 5 percent.

• Journal of the Semiconductor & Display Technology
• /
• v.10 no.3
• /
• pp.75-81
• /
• 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 Ecology and Environment
• /
• v.29 no.4
• /
• pp.361-364
• /
• 2006

The objective of the current study was to characterize and apply multiple regression model relating to vegetation values of the plant species over salt marshes. For each salt marsh community, vegetation and soil variables were investigated in the western coast and the southern coast in South Korea. Osmotic potential of soil and $Cl^-$ content of soil as independent variable had positive and negative influences on vegetation values. Multiple regression model showed that vegetation values of 14 coastal plant communities were determined by pH of soil, osmotic potential of soil and sand content. The multiple regression equation may be applied to the explanation of distribution and abundance of plant communities with exiting ordination plots.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2020.11a
• /
• pp.234-236
• /
• 2020

Content-adaptive training and transmission of the model parameters of neural networks can boost up the SR performance with higher restoration fidelity. In this case, efficient transmission of neural network parameters are essentially needed. Thus, we propose a novel method of compressing the network model parameters based on the training of network model parameters in the sense that the residues of filter parameters and content loss are jointly minimized. So, the residues of filter parameters are only transmitted to receiver sides for different temporal portions of video under consideration. This is advantage for image restoration applications with receivers (user terminals) of low complexity. In this case, the user terminals are assumed to have a limited computation and storage resource.

• Korea-Australia Rheology Journal
• /
• v.12 no.2
• /
• pp.135-141
• /
• 2000

The linear viscoelastic behavior of acrylonitrile-butadiene-styrene (ABS) polymers with different rubber content has been investigated in the frame of a linear viscoelastic model, which takes into account the inter-connectivity of the dispersed rubber particles. The model developed in our previous work has been shown to properly predict the low frequency plateau for the storage modulus, which is generally observed in polymer blends containing core-shell-type impact modifiers. In the present study, further experiments have been carried out on ABS polymers with different rubber content to verify the validity of our linear viscoelastic model. It has been found that our model describes quite properly the rheological behavior of ABS polymers with different rubber content, especially at low frequencies. The experimental data confirm that our model describes the rheological properties of rubber-modified thermoplastic polymers with strong adhesion at the particle/matrix interface more accurately than the Palierne model.