• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.238-241
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• 2003

This paper presents a nonlinear least squares decision feedback equalizer Bilinear systems are attractive because of the ability to approximate a large class of nonlinear systems efficiently. The nonlinearity of channel is modeled using a bilinear system. The algorithms are derived by using the QR decomposition for minimization covariance matrix of prediction error by applying Givens rotation to the bilinear model. Result of computer simulation experiments that compare the performance of the bilinear DFE to two other DFE's in eliminating the intersymbol interference caused by a nonlinear channel are presented In the paper.

• Journal of Advanced Navigation Technology
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• v.11 no.3
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• pp.252-258
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• 2007

There has been a lot of research done in scheme guaranteeing user's mobility and effective resources management to satisfy the requested by users in the wireless/mobile networks. In this paper, we propose a predictive resource allocation scheme based on ARMA(Auto Regressive Moving Average) prediction model to meet QoS requirements(handoff dropping rate) for guaranteeing users' mobility. The proposed scheme predicts the demanded amount of resource in the future time by ARMA time series prediction model, and then reserves it. The ARMA model can be used to take into account the correlation of future handoff resource demands with present and past handoff demands for provision of targeted handoff dropping rate. Simulation results show that the proposed scheme outperforms the existing RCS(Reserved channel scheme) in terms of handoff connection dropping rate and resource utilization.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3029-3045
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• 2017

The main processes of a cognitive radio system include spectrum sensing, spectrum decision, spectrum sharing, and spectrum conversion. Experimental results show that these stages introduce a time delay that affects the spectrum sensing accuracy, reducing its efficiency. To reduce the time delay, the frequency spectrum prediction was proposed to alleviate the burden on the spectrum sensing. In this paper, the deep recurrent neural network (DRNN) was proposed to predict the spectrum of multiple time slots, since the existing methods only predict the spectrum of one time slot. The continuous state of a channel is divided into a many time slots, forming a time series of the channel state. Since there are more hidden layers in the DRNN than in the RNN, the DRNN has fading memory in its bottom layer as well as in the past input. In addition, the extended Kalman filter was used to train the DRNN, which overcomes the problem of slow convergence and the vanishing gradient of the gradient descent method. The spectrum prediction based on the DRNN was verified with a WiFi signal, and the error of the prediction was analyzed. The simulation results proved that the multiple slot spectrum prediction improved the spectrum efficiency and reduced the energy consumption of spectrum sensing.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.6
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• pp.1026-1036
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• 2004

In this study, single-phase heat transfer experiments were conducted with Oblong Shell and Plate heat exchanger using water. An experimental water loop has been developed to measure the single-phase heat transfer coefficient and pressure drop in a vertical Oblong Shell and Plate heat exchanger. Downflow of hot water in one channel receives heat from the cold water upflow of water in the other channel. Similar to the case of a plate heat exchanger, even at a very low Reynolds number, the flow in the Oblong Shell and Plate heat exchanger remains turbulent. The present data show that the heat transfer coefficient and pressure drop increase with the Reynolds number. Based on the present data, empirical correlations of the heat transfer coefficient and pressure drop in terms of Nusselt number and friction factor were proposed. Also, performance prediction analyses for Oblong Shell and Plate heat exchanger were executed and compared with experiments. $\varepsilon$-NTU method was used in this prediction program. Independent variables are flow rates and inlet temperatures. Compared with experimental data, the accuracy of the program is within the error bounds of $\pm$5% in the heat transfer rate.

• Journal of Communications and Networks
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• v.15 no.6
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• pp.589-600
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• 2013

In this paper, we propose a new feedback scheme called mode selection-based feedback by scheduling probability prediction (SPP-MF) for channel state feedback in OFDMA downlink system. We design the scheme such that it determines the more desirable feedback mode among selective feedback by scheduling probability prediction (SPP-SF) mode and bitmap feedback by scheduling probability prediction (SPP-BF) mode, by calculating and comparing the throughputs of the two modes. In both feedback modes, each user first calculates the scheduling probability of each subchannel (i.e., the probability that a user wins the scheduling competition for a subchannel) and then forms a feedback message based on the scheduling probability. Specifically, in the SPP-SF mode, each user reports the modulation and coding scheme (MCS) levels and indices of its best S subchannels in terms of the scheduling probability. In the SPP-BF mode, each user determines its scheduling probability threshold. Then, it forms a bitmap for the subchannels according to the scheduling probability threshold and sends the bitmap along with the threshold. Numerical results reveal that the proposed SPP-MF scheme achieves significant performance gain over the existing feedback schemes.

• Journal of information and communication convergence engineering
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• v.8 no.3
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• pp.273-276
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• 2010

Opportunistic spectrum access (OSA) allows unlicensed users to share licensed spectrum in space and time with no or little interference to primary users, with bring new research challenges in MAC design. We propose a cognitive MAC protocol using statistical channel information and selecting appropriate idle channel for transmission. The protocol based on the CSMA/CA, exploits statistics of spectrum usage for decision making on channel access. Idle channel availability, spectrum hole sufficiency and available channel condition will be included in algorithm statistical information. The model include the control channel and data channel, the transmitter negotiates with receiver on transmission parameters through control channel, statistical decision results (successful rate of transmission) from exchanged transmission parameters of control channel should pass the threshold and decide the data transmission with spectrum hole on data channel. The proposed protocol's simulation will show that proposed protocol does improve the throughput performance via traditional opportunistic spectrum access MAC protocol.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.102-108
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• 2023

Recently in Korea, YouTube stock channels increased rapidly due to the high social interest in the stock market during the COVID-19 period. Accordingly, the role of new media channels such as YouTube is attracting attention in the process of generating and disseminating market information. Nevertheless, prior studies on the market forecasting power of YouTube stock channels remain insignificant. In this study, the market forecasting power of the information from the YouTube stock channel was examined and compared with traditional news media. To measure information from each YouTube stock channel and news media, positive and negative opinions were extracted. As a result of the analysis, opinion in channels operated by media outlets were found to be leading indicators of KOSPI market returns among YouTube stock channels. The prediction accuracy by using logistic regression model show 74%. On the other hand, Sampro TV, a popular YouTube stock channel, and the traditional news media simply reported the market situation of the day or instead showed a tendency to lag behind the market. This study is differentiated from previous studies in that it verified the market predictive power of the information provided by the YouTube stock channel, which has recently shown a growing trend in Korea. In the future, the results of advanced analysis can be confirmed by expanding the research results for individual stocks.

• Proceedings of the Korea Water Resources Association Conference
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• 2000.05a
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• pp.553-558
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• 2000

• Journal of the korean society of oceanography
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• v.37 no.1
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• pp.10-19
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• 2002

The detailed structure of a tidal front and its ebb-to flood variation in the main tidal channel of the Kyunggi Bay in the mid-west coast of Korea were investigated by analyzing CTD data and drifter trajectories collected in late July 1999. A typical tidal front was formed in water about 60 m deep at the mouth of the channel. Isotherms and isohalines in the upper layer above the seasonal pycnocline in the offshore stratified zone inclined upward to the sea surface to form a surface front, while those in the lower layer declined to the bottom front. The location of the front is consistent with $100 S^3/cm^2$ of the mixing index H/U defined by Simpson and Hunter (1974), where H is the water depth and U is the amplitude of tidal current. The potential energy anomaly in the frontal zone varied at an ebb-to flood tidal cycle, showing a minimum at slack water after ebb but a maximum at slack water after flood. This ebb-to flood variation in potential energy anomaly is not accounted for by the mixing index. We conclude that on- and offshore displacement of the water column by tidal advection is responsible for the ebb-to-flood variation in the frontal zone.

• Journal of Advanced Navigation Technology
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• v.19 no.4
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• pp.318-322
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• 2015

In wireless communication networks, most of the prediction techniques are used for predicting the amount of resource required by user's calls for improving their demanding quality of service. However, we propose a channel allocation scheme based on predicting the resources of white spectrum holes for improving the QoS of rental user's spectrum handoff calls for cognitive radio networks in this paper. This method is supported by Wiener predictor to predict the amount of white spectrum holes of license user's free spectrum resources. We classify rental user's calls into initial calls and spectrum handoff calls, and some portion of predicted spectrum-hole resources is reserved for spectrum handoff calls' priority allocation. Simulations show that the performance of the proposed scheme outperforms in spectrum handoff call's dropping rate than an existing method without spectrum hole prediction(11% average improvement in 50% reservation).