• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3133-3151
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• 2012

The optimal price strategy selection of two bounded rational cognitive mobile virtual network operators (MVNOs) in a duopoly spectrum sharing market is investigated. The bounded rational operators dynamically compete to sell the leased spectrum to secondary users in order to maximize their profits. Meanwhile, the secondary users' heterogeneous preferences to rate and price are taken into consideration. The evolutionary game theory (EGT) is employed to model the dynamic price strategy selection of the MVNOs taking into account the response of the secondary users. The behavior dynamics and the evolutionary stable strategy (ESS) of the operators are derived via replicated dynamics. Furthermore, a reward and punishment mechanism is developed to optimize the performance of the operators. Numerical results show that the proposed evolutionary algorithm is convergent to the ESS, and the incentive mechanism increases the profits of the operators. It may provide some insight about the optimal price strategy selection for MVNOs in the next generation cognitive wireless networks.

• Journal of the Speleological Society of Korea
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• no.88
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• pp.38-44
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• 2008

This study aims to identify the efficiency by applying diverse index to the positions of vertex in the network among the network analysis methods in order to identify the relational location features of caves. The first consideration was about the relational location features according to the linking degree and centrality of cave. The second consideration was about the structural equivalence between caves or between caves and the surrounding tourists attractions. A variety of index examined in this study is very efficient for identifying the positions of caves in the network. Furthermore, the relational location features in consideration of surrounding tourists attractions identified the availability of more objective and quantitative expression. In particular, when there are other caves around a cave, it is also very useful to identify the structural equivalence or comparison with other caves.

• Earthquakes and Structures
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• v.26 no.2
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• pp.87-96
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• 2024

This paper proposes a logistic multinomial regression approach to model the spatial cross-correlation of damage probabilities among different damage states in an expanded transportation network. Utilizing Bayesian theory and the multinomial logistic model, we analyze the damage states and probabilities of bridges while incorporating damage correlation. This correlation is considered both between bridges in a network and within each bridge's damage states. The correlation model of damage probabilities is applied to the seismic assessment of a portion of Tehran's transportation network, encompassing 26 bridges. Additionally, we introduce extra daily traffic time (EDTT) as an operational parameter of the transportation network and employ the shortest path algorithm to determine the path between two nodes. Our results demonstrate that incorporating the correlation of damage probabilities reduces the travel time of the selected network. The average decrease in travel time for the correlated case compared to the uncorrelated case, using two selected EDTT models, is 53% and 71%, respectively.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.162-168
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• 2024

VANET (vehicular ad hoc network) refers to the case networks designed for vehicles. Such networks are established among the vehicles which are equipped with communication tools. Within these networks, vehicles are regarded as the network nodes. On time and on schedule transmission of data is of high significance for these networks. In order to accomplish the objective of on-time data transmission, specific electronic equipment is embedded in each vehicle which maintains ad hoc communications among the passengers. Information about traffic, road signs and on-line observation of traffic status can be transmitted via these networks; such data makes it possible for the driver to select the best route to reach his destination. If there are not any infrastructures, two broadcasting approaches can be considered: overflowing and rebroadcasting. The overflowing approach leads to heavy traffic. Hence, the challenge we face is to avoid the broadcasting flood. In this paper, an approach for the management of the broadcasting flood is proposed based on fuzzy theory. The proposed method is assumed to have better performance and efficiency than any other approaches in terms of crash rate, the rate of message success and delay

• Journal of the Economic Geographical Society of Korea
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• v.10 no.4
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• pp.355-376
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• 2007

The aim of this study is to examine the changes of approach methods of research framework in the history of Korean economic geography during the last fifty years($1956{\sim}2005$). The five factors that have influenced Korean economic geography are Korean geography, European, American, and Japanese geography, fundamental theories of economics and business administration, regional problems, and culture. The study of Korean economic geography can be divided into four periods: 'period of cradle of economic geography($1956{\sim}1962$)', 'period of establishment of economic geography(1963$\sim$later 1970s)', 'period of leap of economic geography(the former half of 1980s$\sim$the former half of 1990s)', and 'period of transition of economic geography (since later 1990s)'. And research framework of Korean economic geography has changed from the regional structure theory in 'period of leap' to the spatial system of economies and network theory in 'period of transition'. Spatial system of economies and network theory consists of spatial system of world economies, spatial system of national economies, spatial system of regional economies, spatial network of enterprise economies, and spatial network of information economies.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.784-795
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• 2016

In this paper, we investigate the resource allocation problem in time-varying heterogeneous wireless networks (HetNet) with multi-homing user equipments (UE). The stochastic optimization model is employed to maximize the network utility, which is defined as the difference between the HetNet's throughput and the total energy consumption cost. In harmony with the hierarchical architecture of HetNet, the problem of stochastic optimization of resource allocation is decomposed into two subproblems by the Lyapunov optimization theory, associated with the flow control in transport layer and the power allocation in physical (PHY) layer, respectively. For avoiding the signaling overhead, outdated dynamic information, and scalability issues, the distributed resource allocation method is developed for solving the two subproblems based on the primal-dual decomposition theory. After that, the adaptive resource allocation algorithm is developed to accommodate the timevarying wireless network only according to the current network state information, i.e. the queue state information (QSI) at radio access networks (RAN) and the channel state information (CSI) of RANs-UE links. The tradeoff between network utility and delay is derived, where the increase of delay is approximately linear in V and the increase of network utility is at the speed of 1/V with a control parameter V. Extensive simulations are presented to show the effectiveness of our proposed scheme.

• The Journal of Information Systems
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• v.29 no.2
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• pp.131-147
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• 2020

Purpose The purpose of this study is to develop intelligent vehicle parking distribution system based on LoRa network at the circumstance of traffic congestion during cultural festival in a local city. This paper proposes a parking dispatch and distribution system using a Q-learning algorithm to rapidly disperse traffics that increases suddenly because of in-bound traffics from the outside of a city in the real-time base as well as to increase parking probability in a parking lot which is widely located in a city. Design/methodology/approach The system get information on realtime-base from the sensor network of IoT (LoRa network). It will contribute to solve the sudden increase in traffic and parking bottlenecks during local cultural festival. We applied the simulation system with Queuing model to the Yudeung Festival in Jinju, Korea. We proposed a Q-learning algorithm that could change the learning policy by setting the acceptability value of each parking lot as a threshold from the Jinju highway IC (Interchange) to the 7 parking lots. LoRa Network platform supports to browse parking resource information to each vehicle in realtime. The system updates Q-table periodically using Q-learning algorithm as soon as get information from parking lots. The Queuing Theory with Poisson arrival distribution is used to get probability distribution function. The Dijkstra algorithm is used to find the shortest distance. Findings This paper suggest a simulation test to verify the efficiency of Q-learning algorithm at the circumstance of high traffic jam in a city during local festival. As a result of the simulation, the proposed algorithm performed well even when each parking lot was somewhat saturated. When an intelligent learning system such as an O-learning algorithm is applied, it is possible to more effectively distribute the vehicle to a lot with a high parking probability when the vehicle inflow from the outside rapidly increases at a specific time, such as a local city cultural festival.

• Journal of Korean Library and Information Science Society
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• v.53 no.1
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• pp.191-210
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• 2022

Niklas Luhmann is a sociologist who has had a strong influence on other disciplines. Therefore, it is necessary to examine what Luhmann's theory has influenced on his subsequent researchers. This study analyzed the knowledge network of studies on Niklas Luhmann's theory by follow-up researchers. Bibliographic coupling and co-citation were used as the analysis method of knowledge network. The main results are as follows. First, the language clusters were divided into Latin American / Spanish-speaking regions, Western Europe / Anglo-American regions, Eastern / Northern Europe and other language regions through bibliographic coupling analysis. Second, from the node analysis of bibliographic coupling, It was divided into 2 main cases: where Luhmann's major works were cited; where Luhmann's minor works were cited. Third, it was found that there are the core work groups that are repeatedly cited among Luhmann's works. Fourth, 12 core works were derived from the node analysis of the co-citation network, and appeared in four groups according to themes.

• Journal of Environmental Impact Assessment
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• v.19 no.3
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• pp.307-314
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• 2010

Brebbia's model has been analyzed to develop the appropriate waterworks management system in Korea, and compared with the conventional models such as EPANET, WaterCad, and InfoWorks. The hydraulic theory of the models was analyzed. Each model's numerical techniques, required parameters, input data and operational methodologies, restrictions, practical applicability and other aspects were investigated. In order to check the validity of Brebbia model, the comparative analysis with EPANET, WaterCAD, and InfoWorks models was performed for linear and nonlinear cases. To find out advantages and disadvantages of each model, the modeling was performed for a simple network and for more complicated A city waterworks system, and the three models applicability was examined. Finally, optimal modeling technique and a model suitable for the use in Korea was suggested, and the problems related to present projects of waterworks management system in Korea were analyzed.

• The Transactions of the Korea Information Processing Society
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• v.4 no.1
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• pp.177-183
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• 1997

The cumulative function of the noncentral t distribution calculate power in testing equality of means of two normal populations and confidence intervals for the ratio of population mean to standard deviation. In this paper, the evaluation of the cumulative function of noncentral t distribution is applied to the neural network consists of the multi-layer perception structure and learning process has the algorithm of the backpropagation. Numerical comparisons are made between the Fisher's values and the results obtained by neural network theory.