• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.21-31
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• 2023

In this paper, we focused on the problem of evaluating multi-class classification accuracy and simulation of multiple classifier performance metrics. Multi-class classifiers for sentiment analysis involved many challenges, whereas previous research narrowed to the binary classification model since it provides higher accuracy when dealing with text data. Thus, we take inspiration from the non-linear Support Vector Machine to modify the algorithm by embedding dynamic hyperplanes representing multiple class labels. Then we analyzed the performance of multi-class classifiers using macro-accuracy, micro-accuracy and several other metrics to justify the significance of our algorithm enhancement. Furthermore, we hybridized Enhanced Convolution Neural Network (ECNN) with Dynamic Support Vector Machine (DSVM) to demonstrate the effectiveness and efficiency of the classifier towards multi-class text data. We performed experiments on three hybrid classifiers, which are ECNN with Binary SVM (ECNN-BSVM), and ECNN with linear Multi-Class SVM (ECNN-MCSVM) and our proposed algorithm (ECNNDSVM). Comparative experiments of hybrid algorithms yielded 85.12 % for single metric accuracy; 86.95 % for multiple metrics on average. As for our modified algorithm of the ECNN-DSVM classifier, we reached 98.29 % micro-accuracy results with an f-score value of 98 % at most. For the future direction of this research, we are aiming for hyperplane optimization analysis.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.653-661
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• 2012

High-availability seamless redundancy (HSR) is a redundancy protocol for Ethernet networks that provides two frame copies for each frame sent. Each copy will pass through separate physical paths, pursuing zero fault recovery time. This means that even in the case of a node or a link failure, there is no stoppage of network operations whatsoever. HSR is a potential candidate for the communications of a smart grid, but its main drawback is the unnecessary traffic created due to the duplicated copies of each sent frame, which are generated and circulated inside the network. This downside will degrade network performance and might cause network congestion or even stoppage. In this paper, we present two approaches to solve the above-mentioned problem. The first approach is called quick removing (QR), and is suited to ring or connected ring topologies. The idea is to remove the duplicated frame copies from the network when all the nodes have received one copy of the sent frame and begin to receive the second copy. Therefore, the forwarding of those frame copies until they reach the source node, as occurs in standard HSR, is not needed in QR. Our example shows a traffic reduction of 37.5%compared to the standard HSR protocol. The second approach is called the virtual ring (VRing), which divides any closed-loop HSR network into several VRings. Each VRing will circulate the traffic of a corresponding group of nodes within it. Therefore, the traffic in that group will not affect any of the other network links or nodes, which results in an enhancement of traffic performance. For our sample network, the VRing approach shows a network traffic reduction in the range of 67.7 to 48.4%in a healthy network case and 89.7 to 44.8%in a faulty network case, compared to standard HSR.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.269-276
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• 2016

Public Safty-LTE(Long Term Evolution) is being deployed in the direction of reducing cost by using both of municipal network and commercial network. However, LTE Network is difficult to ensure the survivability during the information communication infrastructure failures. In addition, it is vulnerable in communication coverage of inside buildings and underground. In this study, we propose to implement effectively the network survivability technique through the convergence to the proven technology. As the advent of the IoT Age, smart sensors which are embedded in the environment and the things will be able to provide a useful infrastructure for ensuring the network survivability. Based on the feature of the smart sensor, we designed the sink node architecture to guarantee the network survivability in disaster situation through the convergence of the small cell technology and extension of wireless network coverage technology. The computing power inherent in the environment is a valuable resource that can be utilized in the disaster situation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.4
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• pp.459-466
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• 2020

The sound collected through the multi-rotor unmanned aerial vehicle (UAV) includes the ego noise generated by the motor or propeller, or the wind noise generated during the flight, and thus the quality is greatly impaired. In a multi-rotor UAV environment, both the magnitude and phase of the target sound are greatly corrupted, so it is necessary to enhance the sound in consideration of both the magnitude and phase. However, it is difficult to improve the phase because it does not show the structural characteristics. in this study, we propose a CNN-based complex spectrogram enhancement method that removes noise based on complex spectrogram that can represent both magnitude and phase. Experimental results reveal that the proposed method improves enhancement performance by considering both the magnitude and phase of the complex spectrogram.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2390-2406
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• 2022

Scene text recognition has important application value and attracted the interest of plenty of researchers. At present, many methods have achieved good results, but most of the existing approaches attempt to improve the performance of scene text recognition from the image level. They have a good effect on reading regular scene texts. However, there are still many obstacles to recognizing text on low-quality images such as curved, occlusion, and blur. This exacerbates the difficulty of feature extraction because the image quality is uneven. In addition, the results of model testing are highly dependent on training data, so there is still room for improvement in scene text recognition methods. In this work, we present a natural scene text recognizer to improve the recognition performance from the feature level, which contains feature representation and feature enhancement. In terms of feature representation, we propose an efficient feature extractor combined with Representative Batch Normalization and ResNet. It reduces the dependence of the model on training data and improves the feature representation ability of different instances. In terms of feature enhancement, we use a feature enhancement network to expand the receptive field of feature maps, so that feature maps contain rich feature information. Enhanced feature representation capability helps to improve the recognition performance of the model. We conducted experiments on 7 benchmarks, which shows that this method is highly competitive in recognizing both regular and irregular texts. The method achieved top1 recognition accuracy on four benchmarks of IC03, IC13, IC15, and SVTP.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2771-2778
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• 2014

In this paper, we propose an algorithm that select efficient relay nodes using information of network environment and nodes. The proposed algorithm can be used changeable weight factors as following network environment in node density. The routing protocols adopting store-carry-forward method are used for solving network problems occurred by unstable end-to-end connection in Delay Tolerant Networks(DTNs). Exiting DTN routing algorithms have problems that large latency and overhead because of deficiency of network informations. The proposed algorithm could be provide a solution this problems using changeable weight factor and prediction of network environment. Thus, selected relay nodes work efficiently in unstable and stressed network environment. Simulation results show that enhancement performance as overhead, delivery ratio, average latency compared to exiting DTN routing algorithm.

• Smart Media Journal
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• v.2 no.1
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• pp.8-16
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• 2013

The significant enhancement of the edge portion of computer networks including user-side machines and last mile network links encourages the research of the overlay network based data dissemination systems. Varieties of overlay network based data dissemination systems has distinct purposes, and each of them has a proper structure of an overlay network and a efficient communication protocol. In this paper, overlay network based data dissemination systems for Flash Dissemination, whose target is the distribution of relatively small size data to very large number of recipients within very short time, are explored. Mainly two systems, RECREW and FaReCAST, are introduced and analyzed in the aspects of design considerations for overlay networks and communication protocols. According to evaluations for flash dissemination scenarios, it is observed that the proposed overlay network based flash dissemination systems outperforms the previous overlay network based multicasting systems, in terms of the reliability and the dissemination delay. Moreover, the theoretical analysis of the reliability of data dissemination is provided by analysing FaReCAST.

• Journal of Communications and Networks
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• v.17 no.1
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• pp.47-57
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• 2015

With the ever growing demand of data applications, the joint macro-relay networks are emerging as a promising heterogeneous deployment to provide coverage extension and throughput enhancement. However, the current cellular networks are usually designed to be performance-oriented without enough considerations on the traffic variation, causing substantial energy waste. In this paper, we consider a joint macro-relay network with densely deployed relay stations (RSs), where the traffic load varies in both time and spatial domains. An energy-efficient scheme is proposed to dynamically adjust the RS working modes (active or sleeping) according to the traffic variations, which is called traffic-aware relay sleep control (TRSC). To evaluate the performance of TRSC,we establish an analytical model using stochastic geometry theory and derive explicit expressions of coverage probability, mean achievable rate and network energy efficiency (NEE). Simulation results demonstrate that the derived analytic results are reasonable and the proposed TRSC can significantly improve the NEE when the network traffic varies dynamically.

• Computers and Concrete
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• v.3 no.6
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• pp.439-454
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• 2006

This paper develops an artificial neural network (ANN) model for uniformly loaded restrained reinforced concrete (RC) slabs incorporating membrane action. The development of membrane action in RC slabs restrained against lateral displacements at the edges in buildings and bridge structures significantly increases their load carrying capacity. The benefits of compressive membrane action are usually not taken into account in currently available design methods based on yield-line theory. By extending the existing knowledge of compressive membrane action, it is possible to design slabs in building and bridge decks economically with less than normal reinforcement. The processes involved in the development of ANN model such as the creation of a database of test results from previous research studies, the selection of architecture of the network from extensive trial and error procedure, and the training and performance validation of the model are presented. The ANN model was found to predict accurately the ultimate strength of fully restrained RC slabs. The model also was able to incorporate strength enhancement of RC slabs due to membrane action as confirmed from a comparative study of experimental and yield line-based predictions. Practical applications of the developed ANN model in the design process of RC slabs are also highlighted.

• International journal of advanced smart convergence
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• v.5 no.1
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• pp.23-29
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• 2016

The information is to be considered as important part of any network, the communication nodes within network can able to communicate and transmit information by the means of configured LAN/WAN, or/and using internet technology. Thus, vast enhancement has been made in- exchanging of information over transmission media, this should be beneficial in various disciplines of modern client/server applications but at other side, several massive vulnerabilities have been directly/in-directly associated with them. To resolve the security issues, a security mechanism is proposed which hide the sensitive information of images before transmitting to networks. Random size image samples have used and encrypted to protect them from unauthorized entities. The encryption mechanism manipulates the sample images, and corresponding secret codes are generated which help to protect the images from adversaries. To provide an indestructible security mechanism, cryptography algorithms are deployed and considered as best solutions to keep the secret information of images.