• Proceedings of the IEEK Conference
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• 2000.06b
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• pp.72-75
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• 2000

This paper investigates the complex permittivity of foam materials using the rectangular waveguide. The transmission coefficients of materials inserted in the waveguide are measured with a network analyzer and calculated from the equivalent transmission line model. We use the trial and error method in the acquisition of the complex permittivity.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.4
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• pp.160-166
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• 2002

Since conventional mobile robot control with one module has limitation to solve complex problems, there have been a variety of works on combining multiple modules for solving them. Recently, many researchers attempt to develop mobile robot controllers using artificial life techniques. In this paper, we develop a mobile robot controller using cellular automata based neural networks, where complex tasks are divided to simple sub-tasks and optimal neural structure of each sub-task is explored by genetic algorithm. Neural network modules are combined dynamically using the action selection mechanism, where basic behavior modules compete each other by inhibition and cooperation. Khepera mobile robot simulator is used to verify the proposed model. Experimental results show that complex behaviors emerge from the combination of low-level behavior modules.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.236-240
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• 2022

The main purpose of the study is to analyze the key aspects of state regulation of the hotel and restaurant complex in the system of tourism development and the national economy. The effectiveness of the regulation of the hotel and restaurant complex in the system of development of tourism and the national economy largely depends on the presence of an effective central executive body that would take care of the problems of the development of the industry, the quality and perfection of legal support, a strategic view of programming the development of the industry within the state and regions, as well as administrative mechanisms of public administration, which fully ensure control over the activities of economic entities and the quality of the services they provide. Based on the results of the study, key aspects of state regulation of the hotel and restaurant complex in the system of tourism development and the national economy were identified.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4C
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• pp.241-253
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• 2011

In this paper, a CFNC (Complex Field Network Coding) scheme is presented, which focuses on improving transmission efficiency by reducing time slots that are needed to exchange data frames. Conventional CFNC scheme has the advantage of minimizing the number of time slots required for information exchanges. However, there exists serious performance deterioration because the transmit signals are interfered with each other. Moreover, when CFNC scheme is applied, the estimation and compensation performance of fine frequency offset severely deteriorates due to the multiple frequency offsets in received signal of relay node. In order to overcome these critical problems, we propose an improved CFNC scheme with modified maximum likelihood decision method which uses uplink transmit diversity. Also, we propose an enhanced fine frequency offset estimation method and a corresponding compensation method to deal with the multiple frequency offsets. Corresponding simulation results verify that the proposed methods are able to effectively solve the problems of CFNC scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.9
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• pp.2020-2028
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• 2013

In this paper, we propose a novel analysis and design methodology based on complex network theory for wireless large-scale ad hoc networks. We also enhance the conventional analysis methods which does not sufficiently consider the effect of the wireless communication channels and extend the existing random graph theory by reflecting the wireless communication environments. As a main result, the effect of the network topology such as average degree of each communication node on the network capacity through extensive computer simulations.

• Journal of Sensor Science and Technology
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• v.16 no.5
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• pp.361-368
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• 2007

Small size real-time ECG signal analysis function by QRS-complex detection was put into sensor nodes. Wireless sensor nodes attached on the patient’s body transmit ECG data continuously in normal u-healthcare system. So there are heavy communication traffics between sensor nodes and gateways. New developed platform for real-time analysis of ECG signals on sensor node can be used as an advanced diagnosis and alarming system for healthcare. Sensor node does not need to transmit ECG data all the time in wireless sensor network and to server PC via gateway. When sensor node detects suspicion or abnormality in ECG, then the ECG data in the network was transmitted to the server PC for further powerful analysis. This system can reduce data packet overload and save some power in wireless sensor network. It can also increase the server performance.

• Korean Chemical Engineering Research
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• v.45 no.1
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• pp.25-31
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• 2007

In a petrochemical complex, large amount of hydrogen is produced as a by-product and used as a fuel in petrochemical and oil refinery plants. By recycling this byproduct hydrogen as a raw material, the value of hydrogen can be greatly improved. This paper proposes a design methodology for optimal hydrogen recycle network between plants in petrochemical complex by analyzing the hydrogen pinch, required cost and constraints.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.914-927
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• 2017

Weighted network link prediction is a challenge issue in complex network analysis. Unsupervised methods based on local structure are widely used to handle the predictive task. However, the results are still far from satisfied as major literatures neglect two important points: common neighbors produce different influence on potential links; weighted values associated with links in local structure are also different. In this paper, we adapt an effective link prediction model-local naive Bayes model into a weighted scenario to address this issue. Correspondingly, we propose a weighted local naive Bayes (WLNB) probabilistic link prediction framework. The main contribution here is that a weighted cluster coefficient has been incorporated, allowing our model to inference the weighted contribution in the predicting stage. In addition, WLNB can extensively be applied to several classic similarity metrics. We evaluate WLNB on different kinds of real-world weighted datasets. Experimental results show that our proposed approach performs better (by AUC and Prec) than several alternative methods for link prediction in weighted complex networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3602-3620
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• 2016

Dynamic topology is one of the main influence factors on network performability. However, it was always ignored by the traditional network performability assessment methods when analyzing large-scale mobile ad hoc networks (MANETs) because of the state explosion problem. In this paper, we address this problem from the perspective of complex network. A two-layer hierarchical modeling approach is proposed for MANETs performability assessment, which can take both the dynamic topology and multi-state nodes into consideration. The lower level is described by Markov reward chains (MRC) to capture the multiple states of the nodes. The upper level is modeled as a small-world network to capture the characteristic path length based on different mobility and propagation models. The hierarchical model can promote the MRC of nodes into a state matrix of the whole network, which can avoid the state explosion in large-scale networks assessment from the perspective of complex network. Through the contrast experiments with OPNET simulation based on specific cases, the method proposed in this paper shows satisfactory performance on accuracy and efficiency.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.19 no.7
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• pp.624-630
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• 2006

ZnO deposition parameters are not independent and have a nonlinear and complex property. To propose a method that could verify and predict the relations of process variables, neural network was used. At first, ZnO thin films were deposited by using RF magnetron sputtering process with various conditions. Si, GaAs, and Glass were used as substrates. The temperature, work pressure, and RF power of the substrate were $50\sim500^{\circ}C$, 15 mTorr, and $180\sim210W$, respectively : the purity of the target was ZnO 4 N. Structural properties of ZnO thin films were estimated by using XRD (0002) peak intensity. The structure of neural network was a form of 4-7-1 that have one hidden layer. In training a network, learning rate and momentum were selected as 0.2, 0.6 respectively. A backpropagation neural network were performed with XRD (0002) peak data. After training a network, the temperature of substrate was evaluated as the most important parameter by sensitivity analysis and response surface. As a result, neural network could capture nonlinear and complex relationships between process parameters and predict structural properties of ZnO thin films with a limited set of experiments.