• Journal of Information Management
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• v.36 no.4
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• pp.155-174
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• 2005

Recently, under the pressure of national necessity, the national S&T information system(NTIS) for collecting, managing and distributing various R&D information is under discussion. The close inter-connections and cooperations among elements in R&D process, activity, information and data levels are the basis of national S&T information system. In this paper, we propose a cross reference model of R&D information. The proposed model includes research project, person and output information which are essential in the R&D activities. By using the proposed model, a cross navigating and referencing among R&D information is possible. And various queries on the models from various viewpoints are also possible. XML Topic Map, ISO13250 Standard, is used for development of the proposed model. The efficiencies and further practical usages of proposed model are discussed by demonstrating the proposed model with an example.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.5
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• pp.3-12
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• 2016

Recently, the study on 5G mobile communication systems using the millimeter-wave frequency band have been actively promoted and the importance of compensation of the nonlinearity of power amplifier caused by the characteristics of millimeter-wave frequency propagation attenuation is increasing. In the paper, we propose a piecewise polynomial model based on subdivision coefficient which are characteristics of power amplifier separated linear section and a non-linear section. In addition, the structure of digital predistortion based on the proposed model and direct learning method are proposed to implement a digital predistortion. To verify the proposed model, digital predistortion based on the proposed model and direct learning method for 60 GHz power amplifier using LTE signal implemented in the FPGA. And the hardware test bench measured performance and complexity. The proposed model achieves 3.3 dB gain over the single polynomial model in terms of the ACLR and reduces 7.5 percent in terms of the complexity.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.96-102
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• 2012

An advanced form of the Partitioned Feature-based Classifier with Expertise Table(PFC-ET) is proposed in this paper. As is the case with the PFC-ET, the proposed classifier model, called Classifier Integration Model(CIM), does not use the entire feature vectors extracted from the original data in a concatenated form to classify each datum, but rather uses groups of features related to each feature vector separately. The proposed CIM utilizes a proportion of selected cluster members instead of the expertise table in PFC-ET to minimize the error in confusion table. The proposed CIM is applied to the classification problem on two data sets, Caltech data set and collected terrain data sets. When compared with PFC model and PFC-ET model. the proposed CIM shows improvements in terms of classification accuracy and post processing efforts.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.662-667
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• 2022

Semantic role labeling task(SRL) is to extract predicate and arguments such as agent, patient, place, time. In the previously SRL task studies, a pipeline method extracting linguistic features of sentence has been proposed, but in this method, errors of each extraction work in the pipeline affect semantic role labeling performance. Therefore, methods using End-to-End neural network model have recently been proposed. In this paper, we propose a neural network model using the Biaffine Average Attention model for SRL task. The proposed model consists of a structure that can focus on the entire sentence information regardless of the distance between the predicate in the sentence and the arguments, instead of LSTM model that uses the surrounding information for prediction of a specific token proposed in the previous studies. For evaluation, we used F1 scores to compare two models based BERT model that proposed in existing studies using F1 scores, and found that 76.21% performance was higher than comparison models.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.8
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• pp.748-755
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• 2012

Friction causes self-excited vibration, stick-slip vibration and any other friction-induced phenomena. That kinds of vibrations cause chatter and squeal. In order to predict such vibrations accurately, employing an accurate friction model is very important because a dynamic behavior of a system with friction is dominantly governed by a friction model. A Coulomb friction model is the most widely known model. Coulomb friction model is useful model to obtain analytical solutions of the system with friction and the model gives relatively good simulation result. However, defining a friction force at a stick state in simulation is hard because of the characteristic itself and a Coulomb friction model is discontinuous function between a static and a dynamic friction coefficient. Therefore, applying the Coulomb friction model to a simulation is not appropriate. In order to resolve these problems, an approximated Coulomb friction model was developed using simple and continuous function. However, an approximated Coulomb friction model cannot realize stick. Therefore, an approximated Coulomb friction model cannot describe friction phenomena accurately. In order to analyze a friction phenomenon accurately, a friction model for a simulation was proposed in this paper. A proposed friction model realizes stick and gives reasonably good results compared to results obtained by the simulation employing an approximated Coulomb friction model. Accuracy of a proposed friction model was verified by comparing experimental results.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.156-162
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• 2020

Wireless Sensor Network (WSN) field is mainly studied to monitor and characterize large-scale physical environments to track various environmental or physical conditions, such as temperature, pressure, wind speed and humidity. WSN can be used in various applications such as wild surveillance, military target tracking and monitoring, dangerous environmental exploration and natural disaster relief. We design probabilistic mobile models that apply to mobile ad hoc network mobile environments. A probabilistic shift model proposed by dividing the number of moving nodes and the distance of travel into two categories to express node movement characteristics. The proposed model of movement through simulation was compared with the existing random movement model, ensuring that the width and variation rate of the first node node node node (FND) was stable regardless of the node movement rate. In addition, when the proposed mobile model is applied to the routing protocol, the superiority of network life can be verified from measured FND values. We overcame the limitations of the existing random movement model, showing excellent characteristics in terms of energy efficiency and stable in terms of changes in node movement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3656-3671
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• 2016

Most of the research in the area of wireless communications exclusively relies on simulations. Further, it is essential that the mobility management strategies and routing protocols should be validated under realistic conditions. Most appropriate mobility models play a pivotal role to determine, whether there is any subtle error or flaw in a proposed model. Simulators are the standard tool to evaluate the performance of mobility models however sometimes they suffer from numerous documented problems. To accomplish the widely acknowledged lack of formalization in this domain, a Coloured Petri nets (CPNs) based random direction mobility model for specification, analysis and validation is presented in this paper for wireless communications. The proposed model does not suffer from any border effect or speed decay issues. It is important to mention that capturing the mobility patterns through CPN is challenging task in this type of the research. Further, an appropriate formalism of CPNs supported to analyze the future system dynamic status. Finally the formal model is evaluated with the state space analysis to show how predefined behavioral properties can be applied. In addition, proposed model is evaluated based on generated simulations to track origins of errors during debugging.

• Nuclear Engineering and Technology
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• v.35 no.5
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• pp.399-411
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• 2003

A model predictive control method is applied to design an automatic controller for thermal power control in a reactor core. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, the second optimal control input is not implemented and the procedure to solve the optimization problem is then repeated. The objectives of the proposed model predictive controller are to minimize the difference between the output and the desired output and the variation of the control rod position. The nonlinear PWR plant model (a nonlinear point kinetics equation with six delayed neutron groups and the lumped thermal-hydraulic balance equations) is used to verify the proposed controller of reactor power. And a controller design model used for designing the model predictive controller is obtained by applying a parameter estimation algorithm at an initial stage. From results of numerical simulation to check the controllability of the proposed controller at the $5\%/min$ ramp increase or decrease of a desired load and its $10\%$ step increase or decrease which are design requirements, the performances of this controller are proved to be excellent.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1598-1603
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• 2011

This paper describes an enhancement method for a computational pickup model. The conventional computational pickup model utilizes the ray-trace model and the pinhole model. The conventional model is very useful, however, it suffers from quality degradation of reconstructed images at long distances. To overcome the problem, we propose an accurate pickup model. The proposed model includes integration of the rays incoming to a sensor that generates a pixel, resulting in robustness on the Aliasing artifact. To show the effectiveness of the proposed method, experimental results are carried out. The results indicated that the proposed method is superior to the conventional method.

• Architectural research
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• v.20 no.2
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• pp.53-64
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• 2018

A nonlinear analytical model has been proposed for two-span two-story reinforced concrete frames with relaxed section details. The analytical model is composed of beam, column, and beam-column joint elements. The goal of this study is to develop a simple and light nonlinear model for two-dimensional reinforced concrete frames since research in earthquake engineering is usually involved in a large number of nonlinear dynamic analyses. Therefore, all the nonlinear behaviors are modeled to be concentrated on flexural plastic hinges at the end of beams and columns, and the center of beam-column joints. The envelope curve and hysteretic rule of the nonlinear model for each element are determined based on experimental results, not theoretical approach. The simple and light proposed model can simulate the experimental results well enough for nonlinear analyses in earthquake engineering. Consequently, the proposed model will make it easy to developing a nonlinear model of the entire frame and help to save time to operate nonlinear analyses.