• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.491-499
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• 2011

In this paper, we offer a new strategic portfolio model for national IT R&D project selection in Korea. A risk and return (R-R) portfolio model was developed using an objectively quantified index on the two axes of risk and return, in order to select a strategic project and allocate resources in compliance with a national IT R&D strategy. We strategize using the R-R portfolio model to solve the non-strategy and subjectivity problems of the existing national R&D project selection model. We also use the quantified evaluation index of the IT technology road map (TRM) and the technical level reports (TLR) for the subjectivity of project selection, and try to discover the weights using the analytic hierarchy process (AHP). In addition, we intend to maximize the chance for a successful national IT R&D project, by selecting a strategic portfolio project and balancing the allocation of resources effectively and objectively.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.430-438
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• 2021

The spatial distribution of neutron flux or reaction rate was calculated by cell or mesh tally in traditional Monte Carlo simulation. However, either cell or mesh tally leads to the increase of memory consumption and simulation time. In this paper, the function expansion tally (FET) method was developed in Reactor Monte Carlo code RMC to solve this problem. The FET method was applied to the tallies of neutron flux distributions of uranium block and PWR fuel rod models. Legendre polynomials were used in the axial direction, while Zernike polynomials were used in the radial direction. The results of flux, calculation time and memory consumption of different expansion orders were investigated, and compared with the mesh tally. Results showed that the continuous distribution of flux can be obtained by FET method. The flux distributions were consistent with that of mesh tally, while the memory consumption and simulation time can be effectively reduced. Finally, the convergence analysis of coefficients of polynomials were performed, and the selection strategy of FET order was proposed based on the statistics uncertainty of the coefficients. The proposed method can help to determine the order of FET, which was meaningful for the efficiency and accuracy of FET method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3133-3151
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• 2012

The optimal price strategy selection of two bounded rational cognitive mobile virtual network operators (MVNOs) in a duopoly spectrum sharing market is investigated. The bounded rational operators dynamically compete to sell the leased spectrum to secondary users in order to maximize their profits. Meanwhile, the secondary users' heterogeneous preferences to rate and price are taken into consideration. The evolutionary game theory (EGT) is employed to model the dynamic price strategy selection of the MVNOs taking into account the response of the secondary users. The behavior dynamics and the evolutionary stable strategy (ESS) of the operators are derived via replicated dynamics. Furthermore, a reward and punishment mechanism is developed to optimize the performance of the operators. Numerical results show that the proposed evolutionary algorithm is convergent to the ESS, and the incentive mechanism increases the profits of the operators. It may provide some insight about the optimal price strategy selection for MVNOs in the next generation cognitive wireless networks.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.1
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• pp.1-14
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• 2020

Antenna selection is a method to enhance the performance of spatial multiplexing multiple-input multiple-output (MIMO) systems, which can achieve the diversity order of the full MIMO systems. Although various selection criteria have been studied in the literature, they should be adjusted to the detection operation implemented at the receiver. In this paper, antenna selection methods that optimize the post-processing signal-to-noise ratio (SNR) and eigenvalue are considered for the lattice reduction (LR)-based receiver. To develop a complexity-efficient antenna selection algorithm, the incremental selection strategy is adopted. Moreover, for improvement of performance, an additional iterative selection method is presented in combination with an incremental strategy.

• ETRI Journal
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• v.28 no.1
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• pp.77-83
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• 2006

In order to improve the accuracy of cell selection in heterogeneous cellular systems, this paper proposes a fuzzy multiple-objective decision-based cell selection (FMDCS) strategy. Since heterogeneous cellular systems have different access technologies and multiple traffic classes, the strategy adopts cell type, data rate, coverage, transmission delay, and call arrival rate as evaluation indices, and uses different weight vectors according to the traffic classes of the mobile host. Then, a fuzzy multiple-objective decision algorithm is applied to select the optimal cell from all candidates. This paper also gives an instance analysis and simulation. The instance analysis shows FMDCS makes different selections for different traffic classes. Simulation results of the after-handoff quality-of-service (QoS) show the selected cell can provide MH optimal service.

• Geophysics and Geophysical Exploration
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• v.14 no.3
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• pp.214-219
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• 2011

We perform the frequency-domain waveform inversion based on the residual-selection strategy. In the residual-selection strategy, we classify time-domain residual wavefields into several groups according to the order of absolute amplitudes. Because the residual wavefields are normalized after regularization of the gradient directions within each group, the residual-selection strategy plays a role in enhancing the small-amplitude wavefields, which contributes to improving the deep parts of inverted subsurface images. After classifying residuals in the time domain, they are transformed to the frequency domain. Waveform inversion is performed in the frequency domain using the back-propagation technique which has been popularly used in reverse-time migration. The residual-selection strategy is applied to the SEG/EAGE salt and IFP Marmousi models. Numerical results show that the residual-selection strategy yields better results than the conventional frequency-domain waveform inversion.

• Research in Mathematical Education
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• v.15 no.4
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• pp.357-371
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• 2011

In mathematical problem solving, students may make various errors. In order to draw useful lessons from the errors, and then correct them, we surveyed 24 eighth-grade students' performances in geometrical problem solving according to Casey's hierarchy of errors. It was found that: 1. Students' effect can lead to errors at the stage of "comprehension", "strategy selection", and "skills manipulation"; and 2. Students' geometric schemas also influenced their strategy selection".

• Journal of IKEEE
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• v.22 no.3
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• pp.570-577
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• 2018

With the increasing number of network nodes, traditional client/server node selection mechanisms are under tremendous pressure. In order to select efficient cooperative nodes in a highly dynamic P2P network topology, this article uses greedy algorithm to translate the overall optimization into multiple local optimal problems, and to quickly select service nodes. Therefore, the service node with the largest comprehensive capacity is selected to reduce the transmission delay and improve the throughput of the service node. The final simulation results show that the node selection strategy based on greedy algorithm can effectively improve the overall performance of P2P streaming media system.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.724-729
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• 2001

This paper discusses the composition of the theory of reinforcement learning, which is applied in real-time learning, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line learning method. The individuals are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because the learning process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.

• IE interfaces
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• v.16 no.3
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• pp.291-299
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• 2003

The managerial environment of automobile industry has been rapidly changing, mainly with the tighter standard of legal and environmental regulations, the pressure of cost reduction from the end-user, the various functional improvements of vehicles, and the globalization management. In order to survive in this complicate circumstances, the automakers have strongly pursued the mutual collaboration with the suppliers, especially tier-1, for the optimal selection of parts/materials and the assembly manufacturing processes of the new model development. They prepare the early involvement program for the suppliers during the conceptual design stage, and implement the win-win strategy of technology development activity, in order to improve the value creation. This study considers the strategic technology management of automotive steel sheets makers on the aspects of strategy, processes, human & physical resources, and organization structure. It also suggests the corporate strategies of steel mills, in order to obtain the technology competence.