• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.74-78
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• 2003

In this paper, we have developed a technology-service relationship model which describes the diffusion process of a group of services and relevant technologies, and have applied the developed model to the prediction of the number of subscribers to the next generation mobile service. The technology-service relationship model developed in this paper incorporates the developing process of relevant technologies, a supply-side factor, into the diffusion process of specific services, while many diffusion models and multi-generation diffusion models in previous researches are mainly reflect the demand-side factors. So, the proposed model could effectively applied to the telecommunication services where the developing of the relevant technologies are very essential to the service penetration. In our application, the proposed model provides a competitive substitution between the next generation mobile service and the traditional mobile service.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.241-246
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• 1996

An analytical model to calculate rate of vapor generation due to heterogeneous wall nucleation in flashing flow is developed. In the present model, an important parameter of the vapor generation term, i.e. nucleation site density is calculated by integrating its probability distribution function with respect to active cavity radius. The limits of integration are minimum and maximum active cavity radii, and these are formulated using an active cavity model for nucleate boiling. This formulation, therefore. can statistically account for the effect of surface specific thermo-physical and geometric conditions on the vapor generation rate and flashing inception. For verifying the adequacy of the present model, steady state two-fluid and the bubble transport equations are solved with applicable constitutive equations. The applicable region of the bubble transport equation is also extended to churn-turbulent flow regime to predict interfacial area concentration at high void fraction. Predicted results in terms of axial pressure and void fraction profiles along the channels are compared with experimental data of Super Moby Dick and BNL Reasonable agreements have been achieved and this shows the applicability of the present model to flashing flow analysis.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.179-184
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• 2004

High-resolution satellite imagery are used in various application field such as generation of DEM, orthophto, and three dimensional city model. To define the relation between image and object space, sensor modelling and generation of the epipolar image is essential processes. As the header information or physical sensor model becomes unavailable for the end users due to the national security or commercial purpose, generation of epipolar images without these information becomes one of important processes. In this study, epipolar geometry is generated and analysed by applying two generalized sensor models; parallel and parallel-perspective model Epipolar equation of the parallel model has linear property which is relatively simple; Epipolar geometry of the parallel-perspective model is non-linear. This linear property enable us to generate epipolar image efficiently.

• Transactions of the Korean hydrogen and new energy society
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• v.31 no.5
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• pp.436-443
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• 2020

The performance prediction model of a solid oxide fuel cell stack has been developed using deep neural network technique, one of the machine learning methods. The machine learning has been received much interest in various fields, including energy system mo- deling. Using machine learning technique can save time and cost requried in developing an energy system model being compared to the conventional method, that is a combination of a mathematical modeling and an experimental validation. Results reveal that the mean average percent error, root mean square error, and coefficient of determination (R2) range 1.7515, 0.1342, 0.8597, repectively, in maximum. To improve the predictability of the model, the pre-processing is effective and interpolative machine learning and application is more accurate than the extrapolative cases.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.389-398
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• 2020

Test cases in the existing weapon system software were created manually by the tester analyzing the test items defined in the software integration test procedure. However, existing test case generation method has two limitations. First, the quality of test cases can vary depending on the tester's ability to analyze the test items. Second, excessive time and cost may be incurred in writing test cases. This paper proposes a method to automatically generate test cases based on the requirements model and specifications to overcome the limitations of the existing weapon system software test case generation. Generate test sequences and test data based on the use case event model, a model representing the requirements of the weapon system software, and the use case specification specifying the requirements. The proposed method was applied to 8 target models constituting the avionics control system, producing 30 test sequences and 8 test data.

• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.736-743
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• 2021

Due to COVID-19, the non-face-to-face content market is growing rapidly. However, most of the non-face-to-face content such as webtoons and web novels are produced based on the traditional culture of other countries, not Korean traditional culture. The biggest cause of this situation is the lack of reference materials for creating based on Korean traditional culture. Therefore, the need for materials on traditional Korean culture that can be used for content creation is emerging. In this paper, we propose a generation model of source data based on traditional folk paintings through the fusion of traditional Korean folk paintings and AI technology. The proposed model secures basic data based on folk tales, analyzes the style and characteristics of folk tales, and converts historical backgrounds and various stories related to folk tales into data. In addition, using the built data, various new stories are created based on AI technology. The proposed model is highly utilized in that it provides a foundation for new creation based on Korean traditional folk painting and AI technology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4508-4530
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• 2021

Today distributed data storage service are being widely used. However lack of proper means of security makes the user data vulnerable. In this work, we propose a Randomized Block Size (RBS) model for secure data storage in distributed environments. The model work with multifold block sizes encrypted with the Chinese Remainder Theorem-based RSA (C-RSA) technique for end-to-end security of multimedia data. The proposed RBS model has a key generation phase (KGP) for constructing asymmetric keys, and a rand generation phase (RGP) for applying optimal asymmetric encryption padding (OAEP) to the original message. The experimental results obtained with text and image files show that the post encryption file size is not much affected, and data is efficiently encrypted while storing at the distributed storage server (DSS). The parameters such as ciphertext size, encryption time, and throughput have been considered for performance evaluation, whereas statistical analysis like similarity measurement, correlation coefficient, histogram, and entropy analysis uses to check image pixels deviation. The number of pixels change rate (NPCR) and unified averaged changed intensity (UACI) were used to check the strength of the proposed encryption technique. The proposed model is robust with high resilience against eavesdropping, insider attack, and chosen-plaintext attack.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.504-509
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• 2011

Recently, construction projects are very complicated and diverse such as high-rise buildings and big bridges, etc. These complicated projects call for a system which can effectively generate productive ideas and activities. Value Engineering (V.E.) activity within construction projects is a necessity for systematic design management and to improve construction ability. This need in the construction industry has required a regular implementation of VE into construction projects. For this reason; America, South Korea, and some other nations have adopted VE applications which control the baseline investments of the construction projects. The process of VE activity is a preferred system and a reasonable alternative. In particular, idea generation within these projects is an important stage in the VE job plan. In this study, VE idea patterns are extracted through best practice analysis from VE cases of road construction projects. Next, we suggest an idea hierarchy model to be used in conjunction with VE idea patterns. This model is supported by reasonable idea generation in VE activity of construction projects. Finally, this model could possibly be the outcome of successful VE results.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.3
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• pp.182-187
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• 2018

In this study, 20.8% of a p-type Si bifacial solar cell was used to develop a photovoltaic (PV) module to obtain the maximum power under a limited installation area. The transparent back sheet material was replaced during fabrication with a white one, which is opaque in commercial products. This is very beneficial for the generation of more electricity, owing to the additional power generation via absorption of light from the rear side. A new model is suggested herein to predict the power of the bifacial PV module by considering the backside reflections from the roof and/or environment. This model considers not only the frontside reflection, but also the nonuniformity of the backside light sources. Theoretical predictions were compared to experimental data to prove the validity of this model, the error range for which ranged from 0.32% to 8.49%. Especially, under $700W/m^2$, the error rate was as low as 2.25%. This work could provide theoretical and experimental bases for application to a distributed and microgrid network.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.6
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• pp.414-420
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• 2013

Generation and measurement methods of EG/AD model ice, which is used in KIOST ice model basin are investigated for improvement of its properties. Temperature of seed water, air temperature in the freezing phase and the target air temperature in the tempering phase were changed in the cold room, and the properties of model ice was measured in this conditions. We also verified a conventional measuring method of flexural strength of model ice caused a little measuring error in cold room, so that we suggested a new measuring method that must be used higher supports than double the thickness of the model ice. In this study, we improved the generation and measurement technique of EG/AD model ice, and the developed procedure at cold room can be applied to the KIOST ice model basin.