• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.9
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• pp.1742-1748
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• 2007

In order to provide the convenient access to the mobile services and the efficient utilization of the mobile devices, it is required to devise an intelligent user interface which guarantees the efficient task selection and transition in the limited input/output environments of the mobile devices. In this paper, we propose user task prediction models which are essential for the intelligent user interface, and an accuracy estimation model is also proposed for evaluating the prediction models.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.7
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• pp.639-646
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• 2014

The comparative analysis of near-wall treatment methods that affect the prediction of heat transfer over the gas turbine nozzle guide vane were presented. To achieve this objective, wall-function and low Reynolds number methods, and the transition model were applied and simulated using NASA's C3X turbine vane. The predicted turbine vane surface pressure distribution data using the near-wall treatment methods were found to be in close agreement with experimental data. However, the predicted vane metal temperature and heat transfer coefficient displayed significant differences. Overall, the low Reynolds method and transition model did not offer specific advantages in the prediction of temperature and heat transfer than did the wall-function method. The Reynolds stress model used along with the wall-function method resulted in a relatively high accuracy of prediction of the vane metal temperature and heat transfer coefficient.

• Journal of the Korean Geographical Society
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• v.51 no.4
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• pp.525-539
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• 2016

This study attempts to predict the changes in the spatial distribution of occupational employment in Korea by applying Markov Chain Model. For the purpose we analyze the job-related migration pattern and estimate the transition probability with the last six years job-related migration data. By applying the Chapman-Kolmogorov equation based on the transition probability, we predict the changes in the spatial distribution of occupational employment for the next ten years. The result reveals that the employment of professional jobs is predicted to increase at every city and region except Seoul, while the employment of elementary labor jobs is predicted to increase slightly in Seoul. In particular, Gangwon-do and Chuncheongdo are predicted to increase in the employment of all occupational jobs.

• The KSFM Journal of Fluid Machinery
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• v.17 no.3
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• pp.46-51
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• 2014

In this study, a numerical analysis methodology is studied to predict thermal and flow characteristics of C3X vane with internal cooling. Effects of turbulence models, transition models and viscous work term on temperature and pressure distributions on the vane surface are investigated. These optional terms have few effects on the pressure distributions over the vane surface. However, they have great influence on prediction of the temperature distributions on the vane surface. The combination of k-${\omega}$ based SST turbulence model, ${\gamma}$ transition model and viscous work term are better than RSM turbulence model on prediction of the surface temperature. The average temperature difference between CFD results and experimental results is calculated 2 % at the pressure side and 1 % at the suction side. Furthermore computing time of this combination is half of the RSM turbulence model. When k-${\omega}$ based SST turbulence model and ${\gamma}$ transition model with viscous work term are applied, more accurate predictions of thermal and internal flow characteristics of high pressure turbine are expected.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1694-1701
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• 1997

The residual safety assessment of steel structures, an important subject in practice, is given to much attention. Life prediction in the planning course of steel structures under fatigue loading is mainly based on fatigue design criteria resulting from S-N curves. But for any reason cracks have to be assumed due to fabrication failures or fatigue loading in service which can lead total fracture of structures. The life prediction can be carried out by means of fracture mechanics using Paris-Erdogan equation($da/dN=C {\cdot}{\Delta}K^m$). The paper presents results from charpy test to interpret transition behaviour of charpy energy($A_V$) in a wide temperature range and from constant-load-amplitude test to measure fatigue crack growth of various steels widely used in steel bridges since beginning of 20 centuries in Europe. In the normal service temperature range of steel bridges, the steel S355M shows higher maximum charpy energy($A_{Vmax}$) and lower transition temperature($T_{AVmax/2}$) than other steels considered. The C and m of Paris-Erdogan equation on the steels appear to be correlated, and to be affected by the R-ratios due to crack closure, especially at a low fatigue crack growth rate. Scanning electron microscopy analysis was carried out to interpret an influence of the crack closure effects on the correlation of C and m.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.5
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• pp.1013-1019
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• 2016

This paper describes a novel Context-awareness Markov Chain Prediction (CMCP) algorithm based on movement prediction using Markov chain in Delay Tolerant Network (DTN). The existing prediction models require additional information such as a node's schedule and delivery predictability. However, network reliability is lowered when additional information is unknown. To solve this problem, we propose a CMCP model based on node behaviour movement that can predict the mobility without requiring additional information such as a node's schedule or connectivity between nodes in periodic interval node behavior. The main contribution of this paper is the definition of approximate speed and direction for prediction scheme. The prediction of node movement forwarding path is made by manipulating the transition probability matrix based on Markov chain models including buffer availability and given interval time. We present simulation results indicating that such a scheme can be beneficial effects that increased the delivery ratio and decreased the transmission delay time of predicting movement path of the node in DTN.

• Design & Manufacturing
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• v.17 no.4
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• pp.1-7
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• 2023

In the fabrication of curved multi-display glass for automotive use, the surface roughness of the mold is a critical quality factor. However, the difficulty in detecting micro-cutting signals in a micro-machining environment and the absence of a standardized model for predicting micro-cutting forces make it challenging to intuitively infer the correlation between cutting variables and actual surface roughness under machining conditions. Consequently, current practices heavily rely on machining condition optimization through the utilization of cutting models and experimental research for force prediction. To overcome these limitations, this study employs a surface roughness prediction formula instead of a cutting force prediction model and converts the surface roughness prediction formula into experimental data. Additionally, to account for changes in surface roughness during machining runtime, the theory of position variables has been introduced. By leveraging artificial neural network technology, the accuracy of the surface roughness prediction formula model has improved by 98%. Through the application of artificial neural network technology, the surface roughness prediction formula model, with enhanced accuracy, is anticipated to reliably perform the derivation of optimal machining conditions and the prediction of surface roughness in various machining environments at the analytical stage.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.425-426
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• 2016

In this paper, we proposed an algorithm based on movement prediction using Markov chain in delay tolerant networks(DTNs). The existing prediction algorithms require additional information such as a node's schedule and connectivity between nodes. However, network reliability is lowered when additional information is unknown. To solve this problem, we proposed an algorithm for predicting a movement path of the node by using Markov chain. The proposed algorithm maps speed and direction for a node into state, and predict movement path of the node using transition probability matrix generated by Markov chain. As the result, proposed algorithm show that the proposed algorithms has competitive delivery ratio but with less average latency.

• Journal of Korea Water Resources Association
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• v.33 no.3
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• pp.375-382
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• 2000

The surface hydrology of large watershed is susceptible to several preferred stable states with transitions between stable states induced by stochastic fluctuations. This comes about due to the close coupling of land surface and atmospheric interaction. An interesting and important issue is the duration of residence in each mode. In this study, mean transition tunes between the stable modes are analyzed for the Han River Basin. On the basis of historical data, the nonlinear water balance model is calibrated for the Han River Basin. The transition times between the stable modes in the model are studied based on the stochastic representation of the physical processes and on the calibrated model parameters. This study has implications for prediction of the transition time between stable modes or residence times, that is, the time the system spends in a given stable modes, since this would be equivalent to predicting the duration of drought or wet conditions.

• Journal of computational fluids engineering
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• v.20 no.3
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• pp.1-7
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• 2015

When the steam is used as working fluid in fluid machinery, different from other gases as air, phase transition (steam condensation) can occur and it affects not only the flow fields, but also machine performance & efficiency. Therefore, considering phase transition phenomena in CFD calculation is required to achieve accurate prediction of steam flow and non-equilibrium wet-steam model is needed to simulate realistic steam condensing flow. In this research, non-equilibrium wet-steam model is implemented on in-house code(T-Flow), the flow fields including phase transition phenomena in convergent-divergent nozzle are studied and compared to results of advance researches.