• Journal of Navigation and Port Research
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• v.40 no.5
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• pp.279-284
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• 2016

As the International Maritime English Organization (IMO) model course for Maritime English has been recently revised and updated, the requirements of current changes to both the 2010 STCW Manila Amendments and English education have been actively reviewed. In order to provide practical guidelines for language teaching, a wide range of new pedagogical approaches and their theoretical backgrounds are also suggested. However, considering the current spread of Business English as a Lingua Franca (BELF) and its critical importance in maritime communication, the pedagogical approaches need to be re-evaluated, specifically in terms of teaching pronunciation in order to emphasize clear and effective communication among international interlocutors. Therefore, the core pedagogical elements of pronunciation should be clearly set and provided with consideration for Lingua Franca Core (LFC), which places importance on mutual intelligibility rather than following the rules of native speakers. In this paper, the current trends of BELF in the maritime industry will thus be introduced. Following this, the importance of LFC in maritime communication will be outlined, and its key features will be discussed in terms of effectiveness and clarity of international maritime communications. Finally, a close comparison between LFC and the pronunciation guidelines suggested by the IMO Maritime English model course 3.17 will be conducted, and pedagogical implications for future teaching pronunciation in cross-cultural global maritime industry will be suggested.

• Journal of Advanced Navigation Technology
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• v.14 no.1
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• pp.41-48
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• 2010

Intrusion detection forms a vital component of internet security. To keep pace with the growing trends, there is a critical need to replace single layer detection technology with multi layer detection. Different types of Denial of Service (DoS) attacks thwart authorized users from gaining access to the networks and we tried to detect as well as alleviate some of those attacks. We have proposed a novel cross layer intrusion detection architecture to discover the malicious nodes. The information available across different layers of protocol stack are exploited in order to improve the accuracy of detection. We have used cooperative and distributive anomaly intrusion detection with data mining technique to enhance the proposed architecture. The simulation of the proposed architecture is done in OPNET simulator and the results are analyzed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.4
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• pp.23-27
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• 2010

This paper performs emotion classification test to find out the best parameter of electroencyphalogram(EEG) signal. Linear predictor coefficients, band cross-correlation coefficients of fast Fourier transform(FFT) and autoregressive model spectra are used as the parameters of 10-channel EEG signal. A multi-layer neural network is used as the pattern classifier. Four emotions for relaxation, joy, sadness, irritation are induced by four university students of an acting circle. Electrode positions are Fp1, Fp2, F3, F4, T3, T4, P3, P4, O1, O2. As a result, the Linear predictor coefficients showed the best performance.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.8
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• pp.50-58
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• 2009

Fourth generation mobile communication network have the technology of extensive form include basic service technology and it has been developed from the radio access technology and network topology. Not only fourth generation mobile communication network have basically done new highspeed radio access technology which is suitable to high and low speed environment of transfer, but also it is possible that they have been made for freely vertical handover. ETRI also has made fourth generation mobile communication network which is WiNGS(Wireless Initiative for Next Generation Service) satisfied that demand. This paper is made by lossless handover method through the local retransmission ARQ agent that is one of the main technology of fourth generation mobile communication network. Lossless handover method through local retransmission ARQ agent has been basically made by WiNGS and it was better than original local retransmission of layer by simulation.

• ETRI Journal
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• v.29 no.5
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• pp.569-595
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• 2007

Particularly in wireless communications, link errors severely affect the quality of the services due to the high error probability and the specific error characteristics (burst errors) in the radio access part of the network. In this work, we show that thorough analysis and appropriate modeling of radio-link error behavior are essential to evaluate and optimize higher layer protocols and services. They are also the basis for finding network-aware cross-layer processing algorithms which are capable of exploiting the specific properties of the link error statistics, such as predictability. This document presents the analysis of the radio link errors based on measurements in live Universal Mobile Telecommunication System (UMTS) radio access networks as well as new link error models originating from that analysis. It is shown that the knowledge of the specific link error characteristics leads to significant improvements in the quality of streamed video by applying the proposed novel network- and content-aware cross-layer scheduling algorithms. Although based on live UMTS network experience, many of the conclusions in this work are of general validity and are not limited to UMTS only.

• Journal of Advanced Navigation Technology
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• v.16 no.3
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• pp.426-432
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• 2012

In this paper, we investigate the signal to noise ratio (SNR) estimation performance of Cross quadrature amplitude modulation (QAM), which is being used for asymmetric digital subscriber line (ADSL), very high bit rate digital subscriber line (VDSL), and digital video broadcasting - cable (DVB-C), and has been found to be useful in adaptive modulation and blind equalization. At first, the symbol error rate (SER) performance of Cross QAM is analyzed in Rayleigh fading channel. Then we suggest error vector magnitude (EVM) based SNR estimation utilizing the selected constellation points having different types of decision region from one another, and verify that SNR estimation performance of each points have different performance pattern through simulation. From the simulation results, it has been found that when suggested selected constellation points are used for SNR estimation in Cross QAM, estimation performance is enhanced in additive white Gaussian noise (AWGN) channel or Ricean fading channel.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.190-194
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• 2023

By looking the importance of communication, data delivery and access in various sectors including governmental, business and individual for any kind of data, it becomes mandatory to identify faults and flaws during cyber communication. To protect personal, governmental and business data from being misused from numerous advanced attacks, there is the need of cyber security. The information security provides massive protection to both the host machine as well as network. The learning methods are used for analyzing as well as preventing various attacks. Machine learning is one of the branch of Artificial Intelligence that plays a potential learning techniques to detect the cyber-attacks. In the proposed methodology, the Decision Tree (DT) which is also a kind of supervised learning model, is combined with the different cross-validation method to determine the accuracy and the execution time to identify the cyber-attacks from a very recent dataset of different network attack activities of network traffic in the UNSW-NB15 dataset. It is a hybrid method in which different types of attributes including Gini Index and Entropy of DT model has been implemented separately to identify the most accurate procedure to detect intrusion with respect to the execution time. The different DT methodologies including DT using Gini Index, DT using train-split method and DT using information entropy along with their respective subdivision such as using K-Fold validation, using Stratified K-Fold validation are implemented.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.4
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• pp.466-473
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• 2013

In this paper, a compact planar multi-loop self-resonant coil of high quality factor with a coaxial cross section is proposed for effective wireless charging. The proposed coil has high Q-factor and a resonant frequency of a coil can be easily controlled by adjusting distributed capacitance. For designing the coil, a self-inductance and a distributed capacitance are calculated theoretically. The self-inductance is calculated from the sum of the mutual energies between small circular loops that are made by dividing the cross section of the coil. To verify its properties and calculation results, the self-resonant coils are fabricated by using a coaxial cable with characteristic impedance of $50{\Omega}$. The measured frequencies are very consistent with the calculated ones. In addition, the resonant frequency can be adjusted slightly by the tuning parameter ${\gamma}$. The resonant coils are applied to a tablet PC, the Q-factors of the Tx and Rx resonant coils are 282 and 135, respectively. As a result of measurement when height between the two resonant coils is 4.4 cm, the power transfer efficiency is more than 80 % within a radius of 5 cm.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1075-1086
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• 2018

In this paper a cross-validation algorithm for training probabilistic neural networks (PNNs) is presented in order to be applied to automatic face identification. Actually, standard PNNs perform pretty well for small and medium sized databases but they suffer from serious problems when it comes to using them with large databases like those encountered in biometrics applications. To address this issue, we proposed in this work a new training algorithm for PNNs to reduce the hidden layer's size and avoid over-fitting at the same time. The proposed training algorithm generates networks with a smaller hidden layer which contains only representative examples in the training data set. Moreover, adding new classes or samples after training does not require retraining, which is one of the main characteristics of this solution. Results presented in this work show a great improvement both in the processing speed and generalization of the proposed classifier. This improvement is mainly caused by reducing significantly the size of the hidden layer.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.225-234
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• 2017

Mixed-reality technologies have proven to be valuable in many architecture, engineering and construction / facilities management (AEC/FM) applications. However, its potential of being adapted to facilitate hazard identification and risk communication in construction workplaces has yet to be fully explored. This paper makes an attempt to evaluate the feasibility of applying mixed-reality to enhancing safety risk communication in construction workplaces. Experiments have been designed in which Microsoft HoloLens^® together with a developed application will be used to intervene in the practice of jobsite risk communication. A cross-sectional survey will then be followed to examine the effectiveness and acceptability of this technology through analysis on data collected from participants in the construction industry. The preliminary results show that this emerging HoloLens^® technology, compared to the traditional communication methods (i.e., phone calls, walking up people and talk, and video conferencing), facilitates accurate, prompt safety communication on construction sites. Such findings signify the potential of applying mixed-reality to safety performance enhancement in the construction industry.