• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.203-219
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• 2020

The primary purpose of this study is to identify spatial distribution patterns of co-authoring activities in Korean cadastral science. The analysis showed that a small number of researchers played an essential role in the Korean cadastral co-authorship network. In particular, some authors not only had a significant influence on other nodes in the network but also served as intermediaries between researchers. Moreover, the distance between researchers influenced co-authorship decisions to a limited extent. This study differs considerably from previous studies in that it used spatial analysis techniques to identify spatial distribution patterns of co-authoring activities. However, this research is limited in that it applied only 2019 data to determine the spatial distribution pattern of co-authoring activities. We can overcome this limitation if we analyze the spatial distribution patterns of co-authoring activities using multi-year data in future studies.

• Journal of the Korean association of regional geographers
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• v.20 no.1
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• pp.30-48
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• 2014

Relying on the interaction indices - dominance index, relative strength index and entropy index, this paper analyzes the structural features of urban network in the Seoul metropolitan area with the flows of commuting, business, and freight. Analytical results show that the Seoul metropolitan urban system is vertical, size-dependent, one-way, and the highest city-dominant network rather than horizontal, size-neutral, two-way, complementary one. The network of freight flow is a little bit more symmetrical than the networks of commuting and business. However, the interaction with Seoul is still determinant in all aspects of hierarchical structure, relative strength, and symmetry of flow.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.77-82
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• 2003

The purpose of this study is to develop landslide susceptibility analysis techniques using artificial neural network and to apply the developed techniques to the study area of janghung in Korea. Landslide locations were identified in the study area from interpretation of satellite image and field survey data, and a spatial database of the topography, soil, forest and land use were consturced. The 13 landslide-related factors were extracted from the spatial database. Using those factors, landslide susceptibility was analyzed by artificial neural network methods, and the susceptibility map was made with a e15 program. For this, the weights of each factor were determinated in 5 cases by the backpropagation method, which is a type of artificial neural network method. Then the landslide susceptibility indexes were calculated using the weights and the susceptibility maps were made with a GIS to the 5 cases. A GIS was used to efficiently analyze the vast amount of data, and an artificial neural network was turned out be an effective tool to analyze the landslide susceptibility.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.10
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• pp.19-30
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• 2019

The purpose of this study is to explore ways to efficiently capture the opinions of students who are main users in the planning, planning and design of school facilities. There are many criteria for determining good schools, but in this study, the main purpose of this study was to set up the main users as students, and to analyze the differences between the network and the actual spatial structure (network) created by the hope of students' use of school space, and the direction to overcome the differences. After surveying students' opinions about their satisfaction with school space and their desire to use school space by limiting the survey target to middle and high schools in Seoul, the 'social-space network analysis' was recently established in the social science field. As a result, it was found that the proximity of space and space desired by students in the school varied greatly depending on the geographical conditions, school districts, and the status of the current facilities, and the direction of improvement specialized for each school was found.

• Journal of Korea Technology Innovation Society
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• v.3 no.3
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• pp.36-52
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• 2000

This study takes an issue of efficiency analysis in the presence of network effect utilizing the DEA (Data Envelopment Analysis) framework. Network effect has important policy implication for the regulation of local monopolies which undertake their business through physical network, such as electricity, natural gas, local telephony, etc. If the difference in spatial condition between companies is not controlled properly, the performance comparison and associated incentive regulation bear significant bias. In this study, we propose a methodology to measure the true managerial or technical efficiency apart from efficiency difference accruing from the difference in spatial condition. A series of modified DEA efficiency models are combined to investigate the extent of exogenous and endogenous efficiency component in the Korean natural gas distribution companies. Empirical results show that the network effect plays significant role in determining superficial performance difference.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.314-322
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• 2021

Skeleton-based action recognition has attracted considerable attention in human action recognition. Recent methods for skeleton-based action recognition employ spatiotemporal graph convolutional networks (GCNs) and have remarkable performance. However, most of them have heavy computational complexity for robust action recognition. To solve this problem, we propose a shuffle graph convolutional network (SGCN) which is a lightweight graph convolutional network using pointwise group convolution rather than pointwise convolution to reduce computational cost. Our SGCN is composed of spatial and temporal GCN. The spatial shuffle GCN contains pointwise group convolution and part shuffle module which enhances local and global information between correlated joints. In addition, the temporal shuffle GCN contains depthwise convolution to maintain a large receptive field. Our model achieves comparable performance with lowest computational cost and exceeds the performance of baseline at 0.3% and 1.2% on NTU RGB+D and NTU RGB+D 120 datasets, respectively.

• Journal of Information Processing Systems
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• v.10 no.3
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• pp.459-470
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• 2014

In this paper, the average probability of the symbol error rate (SER) and throughput are studied in the presence of joint spectrum sensing and data transmission in a cognitive relay network, which is in the environment of an optimal power allocation strategy. In this investigation, the main component in calculating the secondary throughput is the inclusion of the spatial false alarms, in addition to the conventional false alarms. It has been shown that there exists an optimal secondary power amplification factor at which the probability of SER has a minimum value, whereas the throughput has a maximum value. We performed a Monte-Carlo simulation to validate the analytical results.

• 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%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.3
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• pp.469-477
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• 2015

In this paper, joint spatial division and reuse (JSDR) scheme is proposed for maximizing network throughput in densely-deployed wireless local area networks equipped with massive antenna array. The proposed JSDR scheme divides the massive spatial space into two subspaces: one is for suppressing the interference from the neighboring access points and another is for sensing the carrier sensing and transmitting the information-bearing signals to intended stations. By using computer simulation, the proposed JSDR can provide 133% higher network throughput, compared to the carrier sensing technique defined in the IEEE 802.11 standard so that the proposed JSDR is suitable for the next generation WLAN systems.

• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1529-1541
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• 2006

Moving objects have been widely employed in traffic and logistic applications. Spatio-temporal aggregations mainly describe the moving object's behavior in the spatial data warehouse. The previous works usually express the object moving in some certain region, but ignore the object often moving along as the trajectory. Other researches focus on aggregation and comparison of trajectories. They divide the spatial region into units which records how many times the trajectories passed in the unit time. It not only makes the storage space quite ineffective, but also can not maintain spatial data property. In this paper, a spatio-temporal aggregation index structure for moving object trajectory in constrained network is proposed. An extended B-tree node contains the information of timestamp and the aggregation values of trajectories with two directions. The network is divided into segments and then the spatial index structure is constructed. There are the leaf node and the non leaf node. The leaf node contains the aggregation values of moving object's trajectory and the pointer to the extended B-tree. And the non leaf node contains the MBR(Minimum Bounding Rectangle), MSAV(Max Segment Aggregation Value) and its segment ID. The proposed technique overcomes previous problems efficiently and makes it practicable finding moving object trajectory in the time interval. It improves the shortcoming of R-tree, and makes some improvement to the spatio-temporal data in query processing and storage.