• Journal of Environmental Science International
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• v.17 no.9
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• pp.957-968
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• 2008

The purpose of this study is to analyze the characteristics of hydraulic behavior of the natural channel flow according to the temporal classification mode, and thus propose the hydraulic analysis method for future channel design. For analysis, the temporal flow characteristics of the channel section was divided into the steady flow and the unsteady flow. For hydraulic analysis, the HEC-RAS model, which is a one-dimensional numerical analysis model, and the SMS-RAM2 model, which is a two-dimensional model, were used and the factors used for analysis of hydraulic characteristics were flood elevation and flow rate. The flow state was analyzed on the basis of the one-dimensional steady flow and unsteady flow for review. In the unsteady flow analysis the flow rate changed by $(-)0.16%{\sim}(+)0.26%$, and the flood elevation varied by $(-)0.35%{\sim}(+)0.51%$ as compared to the values in the steady flow analysis. Given these results, in the one-dimensional flow analysis based on the unsteady flow the flood elevation and flow rate were greater than when the analysis was done on the basis of the steady flow. The flow state was analyzed on the basis of the two-dimensional steady flow and unsteady flow. In the unsteady flow analysis the flow rate varied by $(-)0.16%{\sim}(+)1.08%$, and the flood elevation changed by $(-)0.24%{\sim}(+)0.41%$ as compared to the values in the steady flow analysis. Given these analysis results, in the two dimensional flow analysis based on the unsteady flow, the flood elevation and flow rate were greater than when the analysis was done on the basis of the steady flow.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.15 no.3
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• pp.7-13
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• 2019

To improve the flow distribution at channel locations in the welded plate heat exchanger with "L"-type inflow, the flow visualization of Model 1 was carried out. Besides, the characteristics of flow distribution was investigated experimentally according to the header shape. The inlet flow rate for each channel location was increased at the side channels but decreased at the central channels. In the case of Model 2, which has a slant structure added to the basic header of Model 1, the unevenness of inlet flow increased by 23% from 0.019 to 0.023 as compared to Model 1. On the other hand, Model 3, which has a baffle structure added to Model 2, showed 0.064 unevenness in inlet flow, which was a 36% reduction one compared to Model 1. To improve the distribution at each channel in the welded plate heat exchanger with "L"-type flow, it is necessary to improve the header external shape for the guide of flow as well as the baffle structure for reduction of vortex flow.

• Korea Trade Review
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• v.46 no.5
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• pp.83-98
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• 2021

This study aims to examine the effects of international trade in intermediate input on the implications of international business cycle properties in Korea. To do this, I have extended standard one goods New Keynesian international business cycle model to incorporate the role of intermediate inputs. After constructing the DSGE model, I have analysed the impulse response function and varian decomposition results. The results show that the model could introduce a new channel, that is, "cost channel" like Eyquem and Kamber (2014). In other words, the model has changed the dynamics of aggregate inflation by the cost channel. When the trade in intermediate goods increase, which is measured by openness of foreign input, the volatility of output, consumption and inflation increase two or three times. However, the model itself fails to explain the full account of cycle behavior of historical data, but the results imply that the trade in intermediate input assumption can help to improve the forecasting ability of international business cycle models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.2903-2923
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• 2023

Knowledge recommendation is a type of recommendation system that recommends knowledge content to users in order to satisfy their needs. Although using graph neural networks to extract data features is an effective method for solving the recommendation problem, there is information loss when modeling real-world problems because an edge in a graph structure can only be associated with two nodes. Because one super-edge in the hypergraph structure can be connected with several nodes and the effectiveness of knowledge graph for knowledge expression, a dual-channel hypergraph convolutional neural network model (DCHC) based on hypergraph structure and knowledge graph is proposed. The model divides user data and knowledge data into user subhypergraph and knowledge subhypergraph, respectively, and extracts user data features by dual-channel hypergraph convolution and knowledge data features by combining with knowledge graph technology, and finally generates recommendation results based on the obtained user embedding and knowledge embedding. The performance of DCHC model is higher than the comparative model under AUC and F1 evaluation indicators, comparative experiments with the baseline also demonstrate the validity of DCHC model.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.317-329
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• 2010

In recent years, many sparse estimation methods, also known as compressed sensing, have been developed. However, most of these methods presume that the measurement matrix is completely known. We develop a new blind maximum likelihood method-the expectation-sparse-maximization (ESpaM) algorithm-for models where the measurement matrix is the product of one unknown and one known matrix. This method is a variant of the expectation-maximization algorithm to deal with the resulting problem that the maximization step is no longer unique. The ESpaM algorithm is justified theoretically. We present as well numerical results for two concrete examples of blind channel identification in digital communications, a doubly-selective channel model and linear time invariant sparse channel model.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.91-94
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• 2000

In this paper, the performance of the W-CDMA system with smart antenna is investigated. The realistic wideband channel is assumed, one of which is JTC(Joint Technique Committee) channel model. It is also assumed that multipaths are clustered. The beamforming-RAKE receiver structure of W-CDMA system is proposed, whose performance is analyzed on the assumption of perfect channel estimation. The probability density function (pdf) of SINR(Signal to Interference and Noise Ratio) for different number of antennas and users is presented, and the BER(Bit Error Rate) is presented based on that. As a result, the performance of the W-CDMA system with smart antenna in the realistic wideband channel has been considerably improved.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1604-1610
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• 2004

A steady dilute premixed combustion at transonic speeds in a diverging channel is investigated. The model explores the nonlinear interactions between the near-sonic speed of the flow, the small changes in geometry from a straight channel, and the small heat release due to the one-step first-order Arrhenius chemical reaction. The reactive flow can be described by a nonhomogeneous transonic small-disturbance (TSD) equation coupled with an ordinary differencial equation for the calculation of the reactant mass fraction in the combustible gas. The asymptotic analysis results in the similarity parameters that govern the reacting flow problem. The model is used to study transonic combustion at various amounts of incoming, reactant mass, reaction rates, and channel geometries.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.411-419
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• 2016

This article investigates the problem of distributed channel selection in opportunistic spectrum access networks from a perspective of interference minimization. The traditional physical (PHY)-layer interference model is for information theoretic analysis. When practical multiple access mechanisms are considered, the recently developed binary medium access control (MAC)-layer interference model in the previous work is more useful, in which the experienced interference of a user is defined as the number of competing users. However, the binary model is not accurate in mathematics analysis with poor achievable performance. Therefore, we propose a real-valued one called stochastic MAC-layer interference model, where the utility of a player is defined as a function of the aggregate weight of the stochastic interference of competing neighbors. Then, the distributed channel selection problem in the stochastic MAC-layer interference model is formulated as a weighted stochastic MAC-layer interference minimization game and we proved that the game is an exact potential game which exists one pure strategy Nash equilibrium point at least. By using the proposed stochastic learning-automata based uncoupled algorithm with heterogeneous learning parameter (SLA-H), we can achieve suboptimal convergence averagely and this result can be verified in the simulation. Moreover, the simulated results also prove that the proposed stochastic model can achieve higher throughput performance and faster convergence behavior than the binary one.

• The Transactions of the Korea Information Processing Society
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• v.2 no.3
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• pp.374-381
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• 1995

For designing radio communication systems, radio-channel effects must be considered in order to obtain the desired communication quality, transmitting power, transmission speed and bit error rate. In radio channel, one of major factors that degrade communication quality is multipath fading between transmitting and receiving points. Therefore, a channel model which can describe fading effects correctly is requested. This paper deals with the composition of the channel simulator model that describes multipath fading effects and delay times which occur in the channel. For the performance analysis of the proposed model, trandmitting signal is used in the simulation. From simulation results, it can be shown that probability density function. level crossing rates and average fading-duration time distribution of the faded receive signal are very similar with theoretic values.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.6
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• pp.1032-1037
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• 2006

The channel is one of the precious and limited resources in wireless networks. There are many researches on the channel management. Recently, the optimization problem of guard channels has been an important issue. In this paper, we propose an intelligent channel management technique based on the neural networks. An SRN channel allocation model is developed to generate the learning data for the neural networks and the performance analysis of system. In the proposed technique, the neural network is trained to generate optimal guard channel number g, using backpropagation supervised learning algorithm. The optimal g is computed using the neural network and compared to the g computed by the SRM model. The numerical results show that the difference between the value of 8 by backpropagation and that value by SRM model is ignorable.