• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.172-180
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• 2017

Korean army has been trying to construct a future tactical network in collaboration with TICN at the ground level and the next-generation military satellite system in the space level. However, due to the low bandwidth and high operational cost, the satellite system has the limitation to exchange all kind of tactical information through it. To overcome the limitation, there have been several researches to construct airborne networks. In this paper, we propose an effective interworking architecture and operation scheme between terrestrial tactical networks and aerial relay networks to counteract against the communication breaks of terrestrial terminals. And, we also propose a way to analyze its effectiveness. The experimental results show that the interworking of aerial relay networks can manage the failure situations in terrestrial tactical networks very effectively.

• Journal of Convergence for Information Technology
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• v.11 no.1
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• pp.12-19
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• 2021

For strengthening the national defense, the function of tactical network is essential. tactics and strategies in wartime situations are based on numerous information. Therefore, various reconnaissance devices and resources are used to collect a huge amount of information, and they transmit the information through tactical networks. In tactical networks that which use contention based channel access scheme, high-speed nodes such as recon aircraft may have performance degradation problems due to unnecessary channel occupation. In this paper, we propose a learning-backoff method, which empirically learns the size of the contention window to determine channel access time. The proposed method shows that the network throughput can be increased up to 25% as the number of high-speed mobility nodes are increases.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.4
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• pp.447-458
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• 2013

The present operating system for the atmospheric monitoring network in the city of Seoul, Korea, has been established since the late 90s by the Korean Ministry of Environment (KMOE). In this research, it was evaluated by the multi-statistical approaches through combinations of time series analysis, correlation matrix, and multiple cluster analysis. Finally, road traffic including resuspended materials can be one of the main sources of particulate matter in the atmosphere. Based on its importance, it will be significant challenges in quantitative evaluation of its contribution to airborne concentrations. The future directions for their amendments such as a new management plan for the source of road dust (including car emissions) were devised and proposed based on the statistical judgements derived in this research.

• Journal of the Korean housing association
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• v.26 no.4
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• pp.55-62
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• 2015

The international concern on the inhalable fine dust is continuing to increase. In addition to the toxic properties of the fine dust itself, it can be more dangerous than other environmental factors since the dust pollution is hard to be detected by human sense. Although the information on outdoor air condition can be acquired easily, the indoor dust concentration is another problem because the indoor air condition is influenced by the architectural environment and human activity. It means occupants may be exposed to indoor dust pollution over a long period without being aware. Therefore the indoor dust concentration should be measured separately and visualized as an intuitive information. By visualizing, the indoor dust concentration in each space can be recognized practically in compare with the degree of pollution in adjacent spaces. Besides the visualization outcome can be used as base data for related research such as an analysis of the relation between indoor dust concentration and architectural environment. Meanwhile, with the development of network and micro sensing devices, it became possible to collect wide range of indoor environment data. In this regards, this paper suggests a system for visualization of indoor dust concentration and demonstrates it on an actual space.

• Electronics and Telecommunications Trends
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• v.34 no.6
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• pp.51-60
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• 2019

As a way to further expand and enable the 5G ecosystem, the $3^{rd}$ Generation Partnership Project (3GPP) is considering the development of a 5G new radio (NR)-based non-terrestrial network (NTN). These NTNs are expected to provide ubiquitous 5G services to user's equipment (especially, in Internet of Things/machine-type communications (IoT/MTC) public safety, and critical communications) by extending service coverage to areas not covered by 5G terrestrial networks. To this end, this NTN is developing scenarios to provide 5G services using spaceborne vehicles, such as geosynchronous and low-Earth orbit satellites, and airborne vehicles, such as unmanned aircraft systems, including high-altitude pseudo-satellites. In addition, various technologies are being studied to satisfy new requirements not considered in 5G NR, such as long propagation delay time, large cell coverage, large Doppler effect, and base station movement. In this paper, we present the scenarios, requirements, technical issues and solutions, and standardization planning for NR-based NTN in 3GPP.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1210-1220
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• 2016

As modern warfare has changed into network centered, the ability to share situational awareness among allies become a core competency for performing operational missions. In an airborne environment, it uses a tactical data link such as Link-16 for shared situational awareness. There exist problems when it shares situational awareness over the existing data link that can not allocate slots dynamically or that can not change the number of a slot to be allocated. In addition, there was a problem that can not share this failure so that failed to improves situation awareness because of finite time slot resources. In this paper, we accommodate dynamic slot allocation and changes of slot allocation with mixed structure of TDMA (time division multiple access) and random access. We propose a technique that can be used when available slots are exhausted, and a load balancing method to prevent slot allocation delay when slot requesting or message sending is concentrated on a single subframe.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.807-817
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• 2019

Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiation information of ground surface, geochemistry measuring of the abundance of Potassium, Thorium and Uranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field of nuclear science and human life. The Broyden-Fletcher-Goldfarb-Shanno (BFGS), with its advanced numerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs) provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered by ANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect different architectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRS outputs. The selected approach among of various training methods, with its low iteration cost and nondiagonal scaling allocation is a new powerful algorithm for AGRS data due to its inherent stochastic properties. Experiments were performed by different architectures and trainings, the selected scheme achieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximum performance in compare with different types of optimization strategies and algorithms. The proposed method is capable to be implemented on a cost effective and minimum electronic equipment to present its real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). The advanced adaptation properties and models of neural network, the training of stochastic process and its implementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome of the study shows this method increases the quality of curvature information of AGRS data while cost of the algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate model for Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems.

• IMMUNE NETWORK
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• v.21 no.1
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• pp.9.1-9.8
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• 2021

The most important characteristics of coronavirus disease 2019 (COVID-19) transmission that makes it difficult to control are 1) asymptomatic and presymptomatic transmission, 2) low incidence or lack of dominant systemic symptoms such as fever, 3) airborne transmission that may need a high infectious dose, and 4) super-spread events (SSEs). Patients with COVID-19 have high viral loads at symptom onset or even a few days prior to symptom onset, and most patients with COVID-19 have only mild respiratory symptoms or merely pauci-/null-symptoms. These characteristics of the virus enable it to easily spread to the community because most patients are unaware of their potential infectivity, and symptom-based control measures cannot prevent this type of transmission. Furthermore, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is also capable of airborne transmission in conditions such as aerosol-generating procedures, under-ventilated indoor spaces, and over-crowded areas. In this context, universal mask-wearing is important to prevent both outward and inward transmission until an adequate degree of herd immunity is achieved through vaccination. Lastly, the SSEs of SARS-CoV-2 transmission emphasize the importance of reducing contacts by limiting social gatherings. The above-mentioned transmission characteristics of SARS-CoV-2 have culminated in the failure of long-lasting quarantine measures, and indicate that only highly effective vaccines can keep the communities safe from this deadly, multifaceted virus.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1399-1414
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• 2018

Natural forests are un-manned forests where the artificial forces of people are not applied to the formation of forests. On the other hand, artificial forests are managed by people for their own purposes such as producing wood, preventing natural disasters, and protecting wind. The artificial forests enable us to enhance economical benefits of producing more wood per unit area because it is well-maintained with the purpose of the production of wood. The distinction surveys have been performed due to different management methods according to forests. The distinction survey between natural forests and artificial forests is traditionally performed via airborne remote sensing or in-situ surveys. In this study, we suggest a classification method of forest types using satellite imagery to reduce the time and cost of in-situ surveying. A classification map of natural forest and artificial forest were generated using KOMPSAT-3, 3A, 5 data by employing artificial neural network (ANN). And in order to validate the accuracy of classification, we utilized reference data from 1/5,000 stock map. As a result of the study on the classification of natural forest and plantation forest using artificial neural network, the overall accuracy of classification of learning result is 77.03% when compared with 1/5,000 stock map. It was confirmed that the acquisition time of the image and other factors such as needleleaf trees and broadleaf trees affect the distinction between artificial and natural forests using artificial neural networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.11
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• pp.1011-1022
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• 2014

Currently, the wireless network environment of air node is constructed mainly of ground relay station. However, as the Korean Peninsula is composed of 70% mountainous region, there are multiple shadow zones. This is calling for effective measures to prevent aircraft from losing communication link during low-mid altitude missions. In this article we propose the utilization of Bezier Curve for estimation of aircraft flight path and control method for entering shadow zone. This method successfully estimated aircraft track, and analyzed the existence, disseminated the warning, and took measures to avoid the shadow zone before entering. This article, suggested after simulated experiments, proves that the method enables seamless communication during air operations.