• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2732-2749
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• 2023

Device-to-Device (D2D) communication has received increasing attention and been studied extensively thanks to its advantages in improving spectral efficiency and energy efficiency of cellular networks. This paper proposes a novel relay selection algorithm for multi-hop full-duplex D2D communications underlaying cellular networks. By selecting the relay of each hop in a reverse manner, the proposed algorithm reduces the heavy signaling overhead that traditional relay selection algorithms introduce. In addition, the social domain information of mobile terminals is taken into consideration and its influence on the performance of D2D communications studied, which is found significant enough not to be overlooked. Moreover, simulations show that the proposed algorithm, in absence of social relationship information, improves data throughput by around 70% and 7% and energy efficiency by 64% and 6%, compared with two benchmark algorithms, when D2D distance is 260 meters. In a more practical implementation considering social relationship information, although the proposed algorithm naturally achieves less throughput, it substantially increases the energy efficiency than the benchmarks.

• Journal of information and communication convergence engineering
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• v.22 no.2
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• pp.165-171
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• 2024

In this study, we present a novel approach for enhancing chest X-ray image classification (normal, Covid-19, edema, mass nodules, and pneumothorax) by combining contrastive learning and machine learning algorithms. A vast amount of unlabeled data was leveraged to learn representations so that data efficiency is improved as a means of addressing the limited availability of labeled data in X-ray images. Our approach involves training classification algorithms using the extracted features from a linear fine-tuned Momentum Contrast (MoCo) model. The MoCo architecture with a Resnet34, Resnet50, or Resnet101 backbone is trained to learn features from unlabeled data. Instead of only fine-tuning the linear classifier layer on the MoCopretrained model, we propose training nonlinear classifiers as substitutes for softmax in deep networks. The empirical results show that while the linear fine-tuned ImageNet-pretrained models achieved the highest accuracy of only 82.9% and the linear fine-tuned MoCo-pretrained models an increased highest accuracy of 84.8%, our proposed method offered a significant improvement and achieved the highest accuracy of 87.9%.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.166-171
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• 2024

Recently, there has been an increasing trend in the role of social media in tourism marketing. We analyze changes in tourism marketing trends using tourism marketing keywords through social media networks. The aim is to understand marketing trends based on the analyzed data and effectively create, maintain, and manage customers, as well as efficiently supply tourism products. Data was collected using web data from platforms such as Naver, Google, and Daum through TexTom. The data collection period was set for one year, from December 1, 2022, to December 1, 2023. The collected data, after undergoing refinement, was analyzed as keyword networks based on frequency analysis results. Network visualization and CONCOR analysis were conducted using the Ucinet program. The top words in frequency were 'tourists,' 'promotion,' 'travel,' and 'research.' Clusters were categorized into four: tourism field, tourism products, marketing, and motivation for visits. Through this, it was confirmed that tourism marketing is being conducted in various tourism sectors such as MICE, medical tourism, and conventions. Utilizing digital marketing via online platforms, tourism products are promoted to tourists, and unique tourism products are developed to increase city branding and tourism demand through integrated tourism content. We identify trends in tourism marketing, providing tourists with a positive image and contributing to the activation of local tourism.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.1
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• pp.64-71
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• 2009

TETRA system has been developed focusing on the supporting high-speed and high-capacity data transfer and improving the wireless technology. Hence, TETRA over IP technology became the important basis for supporting compability with various network wireless technologies and high-speed data transfer technologies. For advancing the current TETRA system based on IPv4 network, introduction of IPv6 protocol is necessary. In this paper, we propose an optimized scheme to support IP mobility to IPv6 node when IPv6 protocol is applied to the enviroment ingreated WLAN and TETRA networks. We proposed two scheme using MIPv6 protocol and HMIPv6 protocol respectively. Then, we evaluate performance of the proposed schemes and anlayze the results in order to derive the optimized scheme for the environment integrated WLAN and TETRA networks.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.5
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• pp.99-106
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• 2012

Korea navy has been using the voice-oriented ICS to raise a efficiency of naval ship operation. Recently a multimedia network which are included voice, video and text is under consideration by korean navy. As a basic research to establish the integrated multimedia network of a naval ship, this paper classify the networks in order to apply to an integrated network among the various networks within a naval ship. We also consider the sort and characteristic of the multimedia traffic which is using within the classified networks. To predict the link capacity of switch from number of traffic input source, we suggest a traffic aggregation model. Then we calculate the link capacity of aggregated traffic and analyze a aggregated traffic of Korea major naval ship.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1215-1223
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• 2014

In multi-hop wireless networks, a message transmission path is set up on demand by a route discovery step, where a shortest path is used in general. The shortest path, however, normally uses the nodes near the center area, which causes a high traffic load in that area and reduces the message transmission reliability. We propose a stable routing protocol considering the remaining energy of nodes. Our protocol uses ETX as a link performance estimator and tries to avoid the nodes with smaller energy. By doing this, we can reduce the route failure probability and packet loss. We have evaluated the performance of the proposed protocol using QualNet and compared with AODV and MRFR protocols. The simulation result shows that our protocol has a similar performance as MRFR in terms of end-to-end message reception ratio, average message delay and delay jitter, but outperforms MRFR in terms of traffic load distribution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.183-190
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• 2014

In this paper, we propose a transmission scheme to reduce energy consumption on wireless multi-channel sensor networks. This proposed scheme differentiates the number of usable channels based on a priority. Sensor nodes consume the most energy to transmit data. Also, as transmission distance is far, they consume the more energy. Therefore retransmission due to transmission failure of sensor nodes that are long transmission distance is required more energy consumption. In this paper, we provide a stable transmission environment by allocating a high priority for data that is sent far away. The received data with a high priority is more allocated the number of usable channels. In the experiment results, the receiving failure probability and the restransmission energy consumption of proposed scheme is superior to ones of comparison scheme.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.11
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• pp.67-77
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• 2007

In sensor networks, it is very important to refresh communication keys of sensors in a periodic or on-demand manner. To perform a dynamic key management efficiently, sensor networks usually employ cluster architecture and each CH (Cluster Head) is responsible for key management within its cluster. In cluster-based sensor networks, CHs are likely to be targets of capture attacks, and capture of CHs threatens the survival of network significantly. In this paper, we propose a periodical key refreshment scheme which counteracts against capture of CHs. First, the proposed scheme reduces the threat caused by compromise of CHs by forcing each CH to manage a small number of sensors and changing CH role nodes periodically. Second, the proposed scheme flings attackers into confusion by involving other nodes in a key establishment between BS (Base Station) and a CH. Our numerical analyses showed that the proposed scheme is more secure than other schemes and robust against compromise of CHs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1143-1148
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• 2017

Currently, Artificial Intelligence and Deep Learning are rising as hot social issues, and these technologies are applied to various fields. A good method among the various algorithms in Artificial Intelligence is Convolutional Neural Networks. Convolutional Neural Network is a form that adds Convolution Layers to Multi Layer Neural Network. If you use Convolutional Neural Networks for small amount of data, or if the structure of layers is not complicated, you don't have to pay attention to speed. But the learning should take long time when the size of the learning data is large and the structure of layers is complicated. In these cases, GPU-based parallel processing is frequently needed. In this paper, we developed Convolutional Neural Networks using CUDA, and show that its learning is faster and more efficient than learning using some other frameworks or programs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1127-1136
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• 2017

In wireless networks, the packet loss due to the bit error is misinterpreted as loss due to the congestion state, so TCP congestion control occurs frequently and performance degradation occurs. This degradation also occurs in MPTCP(Multipath TCP), which is an extension protocol of original TCP. In MPTCP, the overall performance of the multipath is degraded. In this paper, we propose a congestion control scheme which measures the bandwidth on each path of MPTCP and reduces the congestion window size by the measured bandwidth when packet loss occurs, in order to solve the MPTCP performance degradation in the wireless environment. We also implemented the proposed congestion control in the Linux kernel and compared it with the original MPTCP in the testbed and real wireless networks. Experimental results show that the proposed congestion control has better throughput performance than original MPTCP congestion control in the wireless environment.