• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.114-130
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• 2021

With the drastic growth of Information and Communication Technology (ICT) industry, global energy consumption is exponentially increased by mobile communications. The huge energy consumption and increased environmental awareness have triggered great interests on the research of dynamic distribution of cell user and traffic, and then designing the energy efficient cellular network. In this paper, we explore the temporal and spatial characteristics of human mobility and traffic distribution using real data set. The analysis results of cell traffic illustrate the tidal effect in temporal and spatial dimensions and obvious periodic characteristics which can be used to design Base Station (BS) dynamic with sleeping or shut-down strategy. At the same time, we designed a new Cell Zooming and BS cooperation mode. Through simulation experiments, we found that running in this mode can save about 35% of energy consumption and guarantee the required quality of service.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.433-436
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• 2008

A demand on the spatial data management has been rapidly increased with the introduction and diffusion process of ITS, Telematics, and Wireless Sensor Network, and many different people use the digital map that offers various thematic spatial data. Spatial data for digital map can manage to tile-based and feature-based data. The existing tile-based digital map management systems have difficult problems of data construction, history management, and updating based on a spatial object. In order to solve these problems, this paper proposed the data model for the feature-based digital map management system that is designed for feature-based seamless map, history management, real-time updating of spatial data, and analyzed the validity and utility of the proposed model.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.866-868
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• 2003

In this paper, we developed those Directory Services based on the Web-Service, because Web-Service environments provide a suitable method to gather requested information in an appropriate way. The proposed architecture cooperate with other OpenLS(Open Location Service) Core Services ( Location Utility Service and Router Determin ation service) and is an interoperability one - it ident ifies those global elements of the global Web-Services network that are required in order to ensure interoperability between Web-Services. In this paper, a new architecture of Directory Service with OpenLS Core Services is proposed and tested in OpenLS Core Services environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3152-3171
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• 2022

This work investigates the physical layer secrecy of a multi-antenna hybrid satellite-terrestrial relay networks (HSTRN) with jamming, in which a satellite aims to make communication with a destination user by means of a relay, along with spatially random eavesdroppers. In order to weaken the signals of eavesdroppers, the conventional relay can also generate intentional interference, besides forwarding the received signal. Shadowed-Rician fading is adopted in satellite link, while Rayleigh fading is adopted in terrestrial link, eavesdropper link and jamming link. The analytical and asymptotic formulas for the system secrecy outage probability (SOP) are characterized. Practical insights on the diversity order of the network are revealed according to the asymptotic behavior of SOP at high signal-to-noise ratio (SNR) regime. Then, analysis of the system throughput is examined to assess the secrecy performance. In the end, numerical simulation results are presented to validate the theoretical analysis and point out: (1) The secrecy performance of the considered network is affected by the channel fading scenario, the system configuration; (2) Decrease of the relay coverage airspace can provide better SOP performance; (3) Jamming from the relay can improve secrecy performance without additional network resources.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.649-654
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• 2023

This paper proposes the design of a neural network structure search model using graph convolutional neural networks. Deep learning has a problem of not being able to verify whether the designed model has a structure with optimized performance due to the nature of learning as a black box. The neural network structure search model is composed of a recurrent neural network that creates a model and a convolutional neural network that is the generated network. Conventional neural network structure search models use recurrent neural networks, but in this paper, we propose GC-NAS, which uses graph convolutional neural networks instead of recurrent neural networks to create convolutional neural network models. The proposed GC-NAS uses the Layer Extraction Block to explore depth, and the Hyper Parameter Prediction Block to explore spatial and temporal information (hyper parameters) based on depth information in parallel. Therefore, since the depth information is reflected, the search area is wider, and the purpose of the search area of the model is clear by conducting a parallel search with depth information, so it is judged to be superior in theoretical structure compared to GC-NAS. GC-NAS is expected to solve the problem of the high-dimensional time axis and the range of spatial search of recurrent neural networks in the existing neural network structure search model through the graph convolutional neural network block and graph generation algorithm. In addition, we hope that the GC-NAS proposed in this paper will serve as an opportunity for active research on the application of graph convolutional neural networks to neural network structure search.

• Journal of the Korean association of regional geographers
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• v.12 no.2
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• pp.245-264
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• 2006

According to many conceptual researches and discourses, development of information-communication technology(ICT) has made great influences upon activities on time and space. But some empirical studies have shown that its influence in the real world is not so great as we may expect In order to avoid these two oppositional views, this paper wants to put interests on socio-spatial relationships or networks, rather than individual phenomena or consciousness, which have been transformed under the influence of ICT. The development of ICT presupposes a creation of information network, and hence the term 'etwork social space' can be used to see its spatial influence, which would be further understood with the theory of actor-network. This paper also suggests that network social space has three strata, that is, 'nstant' 'unctional 'and 'aterial' and that network social space can be emphasized not only as newly emerging social space but also as reconstruction of subjects' identity through his/her participation into information network as its node.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.275-284
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• 2023

Land monitoring involves systematically understanding changes in land use, leveraging spatial information such as satellite imagery and aerial photographs. Recently, the integration of deep learning technologies, notably object detection and semantic segmentation, into land monitoring has spurred active research. This study developed a web service to facilitate such integrations, allowing users to analyze aerial and drone images using CNN models. The web service architecture comprises AI, WEB/WAS, and DB servers and employs three primary deep learning models: DeepLab V3, YOLO, and Rotated Mask R-CNN. Specifically, YOLO offers rapid detection capabilities, Rotated Mask R-CNN excels in detecting rotated objects, while DeepLab V3 provides pixel-wise image classification. The performance of these models fluctuates depending on the quantity and quality of the training data. Anticipated to be integrated into the LX Corporation's operational network and the Land-XI system, this service is expected to enhance the accuracy and efficiency of land monitoring.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6A
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• pp.609-616
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• 2011

The Delay/Disruption Tolerant Network (DTN) is a network designed to operate effectively using the mobility and storage of intermediate nodes under no end-to-end guaranteed network. This new network paradigm is well-suited for networks which have unstable path and long latencies (e.g. interplanetary network, vehicular network). In this paper, we first found that each taxi has its own regularly visiting area and define this property as spatial regularity. We analyze 4000 taxi trace data in Shanghai and show the existence of spatial regularity experimentally. Based on a spatial regularity in urban environment, we present a new DTN routing method. We introduce a Weighted Center (WC) which represents spatial regularity of each node. Through the association with evenly distributed access points (APs) in urban environment, most of vehicles get their grid locations and calculate their WCs. Since our routing method only uses neighbors' WCs for building routing paths, it can be regarded as distributed and practical protocols. Our experiments involving realistic network scenarios created by the traces of about 1500 Shanghai taxies show that our routing method achieves the higher performance compared to ECT, LET by 10%~110%.

• Spatial Information Research
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• v.20 no.1
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• pp.91-103
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• 2012

Recently, there has been much interest in the middleware that can smoothly acquire and analyze Geosensor information which includes sensor readings, location, and its surrounding spatial information. In relation to development of the middleware, researchers have proposed various algorithms for energy-efficient information filtering in Geosensor networks and have proposed Geosensor web technologies which can efficiently mash up sensor readings with spatial information on the web, also. The filtering algorithms and Geosensor Web technologies have contributions on energy-efficiency and OpenAPI, however the algorithms and technologies could not support easy and rapid development of u-GIS applications that need various Geosensor networks. Therefore, we propose a new Geosensor network middleware that can dramatically reduce the time and cost required for development of u-GIS applications that integrate heterogeneous Geosensor networks. The proposed middleware has several merits of being capable of acquiring heterogeneous Geosensor information using the standard SWE and an extended SQL, optimally performing various attribute and spatial operators, and easily integrating various Geosensor networks. Finally, we clarify our middleware's distinguished features by developing a prototype that can monitor environmental information in realtime using spatial information and various sensor readings of temperature, humidity, illumination, imagery, and location.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.1-8
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• 2024

Busan is the 6th largest port city in the world, where nitrogen dioxide (NO₂) emissions from transportation and port industries are significant. This study aims to assess the NO₂ products of the Geostationary Environment Monitoring Spectrometer (GEMS) over Busan using ground-based instruments (i.e., surface in-situ network and Pandora). The GEMS vertical column densities of NO₂ showed reasonable consistency in the spatiotemporal variations, comparable to the previous studies. The GEMS data showed a consistent seasonal trend of NO₂ with the Korea Ministry of Environment network and Pandora in 2022, which is higher in winter and lower in summer. These agreements prove the capability of the GEMS data to monitor the air quality in Busan. The correlation coefficient and the mean bias error between the GEMS and Pandora NO₂ over Busan in 2022 were 0.53 and 0.023 DU, respectively. The GEMS NO₂ data were also positively correlated with the ground-based in-situ network with a correlation coefficient of 0.42. However, due to the significant spatiotemporal variabilities of the NO₂, the GEMS footprint size can hardly resolve small-scale variabilities such as the emissions from the road and point sources. In addition, relative biases of the GEMS NO₂ retrievals to the Pandora data showed seasonal variabilities, which is attributable to the air mass factor estimation of the GEMS. Further studies with more measurement locations for longer periods of data can better contribute to assessing the GEMS NO₂ data. Reliable GEMS data can further help us understand the Asian air quality with the diurnal variabilities.