• Journal of Navigation and Port Research
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• v.40 no.1
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• pp.43-50
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• 2016

Amid of the logistics hub center competition is going to intensifying between the world major port, it is essential to pre-occupied the base in the logistics hub world take advantage of advanced technology of logistics equipment than other ports. In existing container terminal, when container moves the terminal use the omnidirectional and directional antenna in order to exchange data information on the basis of 802.11 wireless network system. Case of loading height of exceeding, the blind sport will occur and a limited frequency channel can't help using in the area. A limited frequency channel usage and nested areas happen to use the closed terminal, it has a great influence to operate the terminal working. In this paper, LTE network is configured provided by the specified company ('L' Corp,.Ltd) and terminal data extracted through LBO (Local Breakout) in the cell site which is configured directly with container terminal operation server. Using this method, container terminal yard equipment operate without overlapping arises with uninterrupted data presented for ways to efficiently. I would suggest both the existing wireless AP LAN configuration of container terminal and new LTE system and applied to the real yard operating devices situations. Through these methods presented comparative the existing network traffic with new constructed LTE configuration. I admired to suggest that wireless network LTE introduction is fundamental factors to get rid of the blind spot, the problem of limited frequency channel and overlapping arises. These essential points can be a continual improving terminal services and more efficient terminal operational management.

• Informatization Policy
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• v.18 no.3
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• pp.25-49
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• 2011

As a way to gather diverse information required for everyday living, the importance of social networks has been growing. Social network services have been spreading rapidly because of diffusion of the Internet, evolution of social network sites, and recognition of the importance of social networks. Recently, the social network service has been evolved based on a new paradigm, Web 2.0, pursuing participation and openness. Following the adoption of Web 2.0 technologies, the social network service allows users to make and maintain new relationships in a more convenient way. Users of the social network service tend to reveal their personal information, and share their ideas and content with other people; in the process they become aware of their existence, feel satisfaction with life and exert influence to others as a member of the society. This study uses higher order factor analysis to analyze factors that affect the intention of using the social network service. A research model was developed with second-order factors including perceived social presence, perceived gratification and perceived social influence. First-order factors are grouped by technical, individual and social factors. Smart PLS 2.0 was used to conduct empirical analysis. The analysis results supported the validity of the research model.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.227-240
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• 2011

New concepts and ideas often result from extensive recombination of existing concepts or ideas. Both researchers and developers build on existing concepts and ideas in published papers or registered patents to develop new theories and technologies that in turn serve as a basis for further development. As the importance of patent increases, so does that of patent analysis. Patent analysis is largely divided into network-based and keyword-based analyses. The former lacks its ability to analyze information technology in details while the letter is unable to identify the relationship between such technologies. In order to overcome the limitations of network-based and keyword-based analyses, this study, which blends those two methods, suggests the keyword network based analysis methodology. In this study, we collected significant technology information in each patent that is related to Light Emitting Diode (LED) through text mining, built a keyword network, and then executed a community network analysis on the collected data. The results of analysis are as the following. First, the patent keyword network indicated very low density and exceptionally high clustering coefficient. Technically, density is obtained by dividing the number of ties in a network by the number of all possible ties. The value ranges between 0 and 1, with higher values indicating denser networks and lower values indicating sparser networks. In real-world networks, the density varies depending on the size of a network; increasing the size of a network generally leads to a decrease in the density. The clustering coefficient is a network-level measure that illustrates the tendency of nodes to cluster in densely interconnected modules. This measure is to show the small-world property in which a network can be highly clustered even though it has a small average distance between nodes in spite of the large number of nodes. Therefore, high density in patent keyword network means that nodes in the patent keyword network are connected sporadically, and high clustering coefficient shows that nodes in the network are closely connected one another. Second, the cumulative degree distribution of the patent keyword network, as any other knowledge network like citation network or collaboration network, followed a clear power-law distribution. A well-known mechanism of this pattern is the preferential attachment mechanism, whereby a node with more links is likely to attain further new links in the evolution of the corresponding network. Unlike general normal distributions, the power-law distribution does not have a representative scale. This means that one cannot pick a representative or an average because there is always a considerable probability of finding much larger values. Networks with power-law distributions are therefore often referred to as scale-free networks. The presence of heavy-tailed scale-free distribution represents the fundamental signature of an emergent collective behavior of the actors who contribute to forming the network. In our context, the more frequently a patent keyword is used, the more often it is selected by researchers and is associated with other keywords or concepts to constitute and convey new patents or technologies. The evidence of power-law distribution implies that the preferential attachment mechanism suggests the origin of heavy-tailed distributions in a wide range of growing patent keyword network. Third, we found that among keywords that flew into a particular field, the vast majority of keywords with new links join existing keywords in the associated community in forming the concept of a new patent. This finding resulted in the same outcomes for both the short-term period (4-year) and long-term period (10-year) analyses. Furthermore, using the keyword combination information that was derived from the methodology suggested by our study enables one to forecast which concepts combine to form a new patent dimension and refer to those concepts when developing a new patent.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.9 no.2
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• pp.83-89
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• 2005

In this paper a new algorithm of learning and evolving artificial neural networks using gene expression programming (GEP) is presented. Compared with other traditional algorithms, this new algorithm has more advantages in self-learning and self-organizing, and can find optimal solutions of artificial neural networks more efficiently and elegantly. Simulation experiments show that the algorithm of evolving weights or thresholds can easily find the perfect architecture of artificial neural networks, and obviously improves previous traditional evolving methods of artificial neural networks because the GEP algorithm imitates the evolution of the natural neural system of biology according to genotype schemes of biology to crossover and mutate the genes or chromosomes to generate the next generation, and the optimal architecture of artificial neural networks with evolved weights or thresholds is finally achieved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.735-748
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• 2014

The fault-tolerance routing problem is one of the most important issues in the application of the Internet of Things, and has been attracting growing research interests. In order to maintain the communication paths from source sensors to the macronodes, we present a hybrid routing scheme and model, in which alternate paths are created once the previous routing is broken. Then, we propose an improved efficient and intelligent fault-tolerance algorithm (IEIFTA) to provide the fast routing recovery and reconstruct the network topology for path failure in the Internet of Things. In the IEIFTA, mutation direction of the particle is determined by multi-swarm evolution equation, and its diversity is improved by the immune mechanism, which can improve the ability of global search and improve the converging rate of the algorithm. The simulation results indicate that the IEIFTA-based fault-tolerance algorithm outperforms the EARQ algorithm and the SPSOA algorithm due to its ability of fast routing recovery mechanism and prolonging the lifetime of the Internet of Things.

• Korean Chemical Engineering Research
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• v.53 no.5
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• pp.627-631
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• 2015

Various solid structures were prepared by electrospray technique. In this process, liquid flows out from a capillary nozzle under a high electrical potential and is subjected to an electric field, which causes elongation of the meniscus to form a jet. In our study, by controlling the amount of polyvinyl pyrrolydone in precursor solution, the jet either disrupted into droplets for the formation of spherical particles or was stretched in the electric field for the formation of fibers. During the electrospray process, the ethanol solvent was evaporated and induced the solidification of precursors, forming solid particles. The evaporation of ethanol solvent also enhanced the mass transport of solutes from the inner core to the solid shell, which facilitated fabrication of porous and hollow structure. The network structures were also prepared by heating the collector.

• International Commerce and Information Review
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• v.5 no.1
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• pp.3-20
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• 2003

IT evolution and the e-business has emerged as a new economic activity and beyond the time and space limitations. But the enterprises located in GangWon-Do area have been too inactive in their willingness and readiness to adopt e-business models and processes owing to the lack of the directions of e-business, the insufficient network infrastructures and capitals, etc. In this circumstance, as part of this research, this papers have conducted a survey on the e-business and information conditions and status among the enterprises located in GangWon-Do Chuncheon area. In conclusions, this study on the informatization of the enterprises and e-business enlarge strategies for building competition of local enterprises located in GangWon-Do Chuncheon area.

• Journal of IKEEE
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• v.22 no.1
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• pp.216-222
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• 2018

Long-range wireless power transmission technology goes beyond mere cell phones and small appliances, and is the core technology of 4'th industrial revolution such as robot, electric car, and IoT sensor network. In this paper, we will explore the evolution of long-range wireless power transmission technologies that have already become commercially available, with rapid advances in technology, beyond the traditional short-range technology that has become technologically common. Through this, it is intended to check the domestic research level and progress by identifying core technologies and technical challenge.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.27-30
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• 2000

Many human inventions were inspired by nature. The artificial neural network is one example. Another example is Genetic Algorithms(GA). GAs search by simulating evolution, starting from an initial set of solutions or hypotheses, and generating successive "generations" of solutions. This particular branch of AI was inspired by the way living things evolved into more successful organisms in nature. To simulate the process of GA in a computer, we must simulate many times according to varying many GA parameters. This paper describes the implementation of Java Package for efficient applications on Genetic Algorithms, called "JavaGA". The JavaGA used as a application program as well as applet provides graphical user interface of assigning major GA parameters.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.113-117
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• 1998

We propose a way to show the inherent learning complexity for the multilayer perceptron. We display the solution space and the error surfaces on the input space of a single neuron with two inputs. The evolution of its weights will follow one of the two error surfaces. We observe that when we use the back-propagation(BP) learning algorithm (1), the wight cam not jump to the lower error surface due to the implicit continuity constraint on the changes of weight. The self-relaxation approach is to explicity find out the best combination of all neurons' two error surfaces. The time complexity of training a multilayer perceptron by self-relaxationis exponential to the number of neurons.