• Journal of Korean Institute of Industrial Engineers
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• v.27 no.4
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• pp.337-344
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• 2001

As cost invested in developing the specified technology is increasing, investors are paying more attention to cost to benefit analysis (CBA). One of the basic elements of CBA for new technological development is the diffusion pattern of demand of such technology. Many studies of technology evaluation have adopted a single generation model to simulate the diffusion pattern of demand. This approach, however, considers the diffusion of the new technology itself, not taking into account a newer generation that can replace the one just invented. In this paper, we show how a multi-generation technology diffusion model can be applied for more accurate CBA for information technology. Monte Carlo simulation is performed to find influential factors on the CBA of a Cybernetic Building System.

• The Journal of Society for e-Business Studies
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• v.17 no.2
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• pp.63-72
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• 2012

The Korean telecommunications market has been expanding swiftly, these days, to be saturated. In this environment, the upcoming mobile telecommunication market, where 4G service was introduced this year, is becoming more substitutive and competitive. Thus, the demand forecasting of 4G service is very difficult, while it is critical to market success. This paper adopts a multi-generation diffusion model to capture the diffusion and substitution patterns for two successive generation of technological services, i.e., 3G and 4G mobile telecommunications services. The three parameters, i.e., the coefficient of innovation, the coefficient of imitation, and the coefficient of market potential, used in the multi-generation diffusion model based on Norton and Bass[11] are obtained by inference from similar substitutive relations between older and newer telecommunication services to 3G and 4G services. The simulation results show that the Bass type multi-generation model can be successfully applied to the demand forecasting of newly introduced 4G mobile telecommunication service.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.1
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• pp.87-99
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• 2004

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 Technology Innovation Conference
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• 2003.02a
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• pp.173-190
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• 2003

Demand forecasting is essential in establishing national and corporate strategy as well as the management of their resource. We forecast demand for multi-generation product using discrete choice model combining diffusion model The discrete choice model generally captures consumers'valuation of the product's qualify in the framework of a cross-sectional analysis. We incorporate diffusion effects into a discrete choice model in order to capture the dynamics of demand for multi-generation products. As an empirical application, we forecast demand for worldwide DRAM (dynamic random access memory) and each of its generations from 1999 to 2005. In so doing, we use the method of 'Technological Forecasting'for DRAM Density and Price of the generations based on the Moore's law and learning by doing, respectively. Since we perform our analysis at the market level, we adopt the inversion routine in using the discrete choice model and find that our model performs well in explaining the current market situation, and also in forecasting new product diffusion in multi-generation product markets.

• 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.

• Smart Media Journal
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• v.13 no.2
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• pp.9-15
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• 2024

In this paper, a Diffusion Multi-step Classifier (DMC) is proposed to address the imbalance issue in credit prediction. DMC utilizes a Diffusion Model to generate continuous numerical data from credit prediction data and creates categorical data through a Multi-step Classifier. Compared to other algorithms generating synthetic data, DMC produces data with a distribution more similar to real data. Using DMC, data that closely resemble actual data can be generated, outperforming other algorithms for data generation. When experiments were conducted using the generated data, the probability of predicting delinquencies increased by over 20%, and overall predictive accuracy improved by approximately 4%. These research findings are anticipated to significantly contribute to reducing delinquency rates and increasing profits when applied in actual financial institutions.

• Journal of Information Technology Applications and Management
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• v.24 no.2
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• pp.81-96
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• 2017

Forecasting long-term mobile service demand is inevitable to establish an effective frequency management policy despite the lack of reliability of forecast results. The statistical forecasting method has limitations in analyzing how the forecasting result changes when the scenario for various drivers such as consumer usage pattern or market structure for mobile communication service is changed. In this study, we propose a dynamic model of the mobile communication service market using system dynamics technique and forecast the future demand for long-term mobile communication subscriber based on the dynamic model, and also experiment on the change pattern of subscriber demand under various scenarios.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.6
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• pp.1-7
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• 2015

Most of chloride diffusion models based on finite difference method (FDM) could not express the diffusion in horizontal direction at each elevation. To overcome these weakness, two dimensional chloride ion penetration model based on finite element method (FEM) to be able to combine various multi-physics simultaneously was suggested by introducing moving mesh technique. To avoid the generation of mesh being able to be distorted depending on the relative movement of water level to static concrete, a rectangular type of mesh was intentionally adopted and the total number of meshes was empirically selected. The simulated results showed that the contents of surface chloride decreased following to the increase of elevation in the top part of low sea level, whereas there were no changes in the bottom part of low level. In the DuraCrete model, the diffusion coefficient of splashed zone is generally smaller than submerged zone, whereas the trend of Life365 model is reverse. Therefore, it could be understood that the developed model using moving mesh technique effectively reflects $DuraCrete^{TM}$ model rather than $Life365^{TM}$ model. In the future, the model will be easily expanded to be combined with various multi-physics models considering water evaporation, heat of hydration, irradiation effect of sun and so on because it is based on FEM.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.455-462
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• 2024

In the construction industry, known for its dynamic and hazardous environments, there exists a crucial demand for effective safety incident prevention. Traditional approaches to monitoring on-site safety, despite their importance, suffer from being laborious and heavily reliant on subjective, paper-based reports, which results in inefficiencies and fragmented data. Additionally, the incorporation of computer vision technologies for automated safety monitoring encounters a significant obstacle due to the lack of suitable training datasets. This challenge is due to the rare availability of safety accident images or videos and concerns over security and privacy violations. Consequently, this paper explores an innovative method to address the shortage of safety-related datasets in the construction sector by employing generative artificial intelligence (AI), specifically focusing on the Stable Diffusion model. Utilizing real-world construction accident scenarios, this method aims to generate photorealistic images to enrich training datasets for safety surveillance applications using computer vision. By systematically generating accident prompts, employing static prompts in empirical experiments, and compiling datasets with Stable Diffusion, this research bypasses the constraints of conventional data collection techniques in construction safety. The diversity and realism of the produced images hold considerable promise for tasks such as object detection and action recognition, thus improving safety measures. This study proposes future avenues for broadening scenario coverage, refining the prompt generation process, and merging artificial datasets with machine learning models for superior safety monitoring.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.33-36
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• 2008

The transient behavior of a passive air breathing direct methanol fuel cell (DMFC) operated on vapor-feeding mode is studied in this paper. It generally takes 30 minutes after starting for the cell response to come to its steady-state and the response is sometimes unstable. A mathematical dynamic one-dimensional model for simulating transient response of the DMFC is presented. In this model a DMFC is decomposed into its subsystems using lumped model and divided into five layers, namely the anodic diffusion layer, the anodic catalyst layer, the proton exchange membrane (PEM), the cathodic catalyst layer and the cathodic diffusion layer. All layers are considered to have finite thickness, and within every one of them a set of differential-algebraic governing equations are given to represent multi-components mass balance, such as methanol, water, oxygen and carbon dioxide, charge balance, the electrochemical reaction and mass transport phenomena. A one-dimensional, isothermal and mass transport model is developed that captures the coupling between water generation and transport, oxygen consumption and natural convection. The single cell is supplied by pure methanol vapor from a methanol reservoir at the anode, and the oxygen is supplied via natural air-breathing at the cathode. The water is not supplied from external source because the cell uses the water created at the cathode using water back diffusion through nafion membrane. As a result of simulation strong effects of water transport were found out. The model analysis provides several conclusions. The performance drop after peak point is caused by insufficiency of water at the anode. The excess water at the cathode makes performance recovery impossible. The undesired crossover of the reactant methanol through the PEM causes overpotential at the cathode and limits the feeding methanol concentration.