• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12B
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• pp.1049-1057
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• 2006

Overlay Multicast is an effective method for efficient utilization of system resources and network bandwidth without using hardware customization. Unlike in IP multicast, multicast tree reconstruction is required when non-leaf node leaves or fails. In this paper, we propose a proactive approach to solve this defect by using a resource reservation of the out degrees. This allows children of non-leaf node to connect to its new parent node immediately when its parent node leaves or fails. In our proposal, a proactive route maintenance gives a fast recovery time and reduces a delay effect in the new route. The simulation results show that our proposal takes shorter period of time than the other algorithms to reconstruct a similar tree and that it is a more effective way to deal with a lot of nodes that have lost their parent nodes.

• Journal of KIISE
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• v.44 no.12
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• pp.1258-1268
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• 2017

Capturing real-time daily information on food prices is invaluable to help policymakers and development organizations address food security problems and improve public welfare. This study analyses the possible use of large-scale online data, available due to growing Internet connectivity in developing countries, to provide updates on food security landscape. We conduct a case study of Indonesia to develop a time-series prediction model that nowcasts daily food prices for four types of food commodities that are essential in the region: beef, chicken, onion and chilli. By using Twitter price quotes, we demonstrate the capability of social data to function as an affordable and efficient proxy for traditional offline price statistics.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.3
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• pp.288-293
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• 2010

This paper presents to calculate the lethality of missile for the simulation test program and to verify the simulation results. In order to calculate a reliable lethality we need may data and experiments of fuse and warhead, but in reality it is hard to perform a task. Therefore, this paper obtained from the reference paper to analyze the lethality data for the calculation of the lethality. We form the 6 DOF simulation model using the MATLAB/SIMULINK. And formed the autopilot algorithm using the vertical and horizontal acceleration feedback and PNG (Proportional Navigation Guidance) command be used to the guidance algorithm. Finally, we evaluate the results about three cases, front launch, side launch and rear launch to simulate the simulation program, and the target is designed to have a constant speed and direction.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.10
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• pp.884-892
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• 2014

In this paper, a meta model using neural network substituting for the simulator aerodynamic database is proposed to improve simulation fidelity near the critical flight area and real-time performance. It is shown that the accuracy of the meta model is relatively higher than the existing table lookup methods for arbitrary nonlinear database and the calculation speed is also improved for a specific F-16 maneuver simulation. The increase in the number of hidden nodes in the meta model for better accuracy of database representations causes a delay in function generation due to increased time required for computing exponential functions. In order to make up this drawback, we additionally study the fast exponential function method.

• Korean Journal of Construction Engineering and Management
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• v.14 no.1
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• pp.63-70
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• 2013

A judgment on the redevelopment projects' predicted profitability is an essential decision-making element for the success of the redevelopment projects. It is necessary to review the literature on profitability of redevelopment project and draw risk factors that could affect profitability through the risk analysis based on surveys. It is also necessary to judge profitability prediction toward the business value of the redevelopment project in the planning phase according to the risk analysis results which can affect the profitability prediction. In order to prevent the growing difficulties in executing the projects, a profitability prediction model is proposed using the method of management and disposal based on a proportional calculation that can estimate the share of expenses in order to judge profitability in the planning phase. With the improvement of profitability prediction models, it is possible to appropriately judge profitability in the planning phase in order to allow the prevention of suspension, reduction of project term, reduction of cost, and making of rational decisions.

• Korean Journal of Construction Engineering and Management
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• v.19 no.2
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• pp.25-37
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• 2018

In recent times, private sector allocates the risk between private sector investors in terms of equity transaction and agreement transaction. The additional risk-allocation have made the cash flows of private sector investors fluctuated and some of the PPP projects delayed. Therefore, analyzing the impact of the risk reallocation between private sector investors on their cash flows is critical for encouraging the private sector participants. In this study, a model to evaluate the financial viability of PPP project is developed based on the discounted cash flow analysis. The model can analyze the variability by equity and agreement transaction by identifying key variables of equity transaction, influence factors of agreement transaction, and relationship between the transactions and investor's profitability. It is expected that the private sector can determine the investment decision for PPP projects when the risk reallocation is occurred.

• Journal of the Korean earth science society
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• v.26 no.7
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• pp.706-713
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• 2005

Subsurface oceanic data (Z20; Depth of $20^{\circ}C$ isotherm and WWV; Warm Water Volume) from the tropical Pacific Ocean from 1980 to 2004 were utilized to examine upper ocean variations in relation to E1 Nino. Time series analysis using EOF, composite, and cross-correlation methods indicated that there are significant time delays between subsurface oceanic parameters and the Nino3.4 SST. It implied that Z20 and WWV would be more reliable predictors of El Nino events. Based on analyzed results, we also constructed neural network model to predict the Nino3.4 SST from 1996 to 2004. The forecasting skills for the model using WWV were statistically higher than that using the trade wind except for short range forecasting less than 3 months. This model greatly predicted SST than any other previous statistical model, especially at lead times of 5 to 8 months.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.181-188
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• 2014

Heterogeneous physical systems and computational devices are incorporated on a large-scale in a CPS (cyber-physical system) environment. Simulations can be useful for the reliable behaviors of CPSs. Time synchronization is one of major technical issues for the simulations. In the CPS, distributed systems control themselves by interacting with each other during runtime. When some simulation models have high complexity, wrong control commands as well as incorrect data can be exchanged due to the time error. We propose a time synchronization algorithm for the hybrid model that has characteristics of both continuous time systems and discrete event systems. In addition, we develop a CPS simulator based on our algorithm. For the verification of the algorithm and the execution of the simulator, we develop an example hybrid model and simulate considering user controls as well as interactions among the distributed systems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.105-113
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• 2007

In this paper, we propose the matching pursuit with damping factors, a new sinusoidal model improving the matching pursuit, for the codecs based on sinusoidal model. The proposed model defines damping factors by using a correlativity of parameters between the current and adjacent frame, and estimates sinusoidal parameters more accurately in analysis frame by using the matching pursuit according to damping factor, and synthesizes the final signal. Then it is possible to model efficiently without interpolation schemes. The proposed sinusoidal model shows a better speech quality without an additional delay than the conventional sinusoidal model with interpolation methods. Through the SNR(signal to noise ratio), the MOS(Mean Opinion Score), LR(Itakura-Saito likelihood ratio), and CD(cepstral distance), we compare the performance of our model with that of matching pursuit using interpolation methods.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.5
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• pp.575-589
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• 2020

In recent years, Shield TBM construction has been continuously increasing in domestic tunnels. The main excavation tool in the shield TBM construction is a disc cutter which naturally wears during the excavation process and significantly degrades the excavation efficiency. Therefore, it is important to know the appropriate time of the disc cutter replacement. In this study, it is proposed a predictive model that can determine yes/no of disc cutter replacement using machine learning algorithm. To do this, the shield TBM machine data which is highly correlated to the disc cutter wears and the disc cutter replacement from the shield TBM field which is already constructed are used as the input data in the model. Also, the algorithms used in the study were the support vector machine, k-nearest neighbor algorithm, and decision tree algorithm are all classification methods used in machine learning. In order to construct an optimal predictive model and to evaluate the performance of the model, the classification performance evaluation index was compared and analyzed.