• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.427-435
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• 2010

We extracted core terms by constructing scientific item networks from textbooks, analyzing their structures, and investigating the connected information and their relationships. For this research, we chose three high-school textbooks from different publishers for each three subjects, i.e, Science, Biology I and Biology II, to construct networks by linking scientific items in each sentence, where used items were regarded as nodes. Scientific item networks from all textbooks showed scare-free character. When core networks were established by applying k-core algorithm which is one of generally used methods for removing lesser weighted nodes and links from complex network, they showed the modular structure. Science textbooks formed four main modules of physics, chemistry, biology and earth science, while Biology I and Biology II textbooks revealed core networks composed of more detailed specific items in each field. These findings demonstrate the structural characteristics of networks in textbooks, and suggest core scientific items helpful for students' understanding of concept in Science and Biology.

• Journal of Communications and Networks
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• v.17 no.6
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• pp.549-557
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• 2015

Mobile cellular networks are becoming increasingly complex to manage while classical deployment/optimization techniques and current solutions (i.e., cell densification, acquiring more spectrum, etc.) are cost-ineffective and thus seen as stopgaps. This calls for development of novel approaches that leverage recent advances in storage/memory, context-awareness, edge/cloud computing, and falls into framework of big data. However, the big data by itself is yet another complex phenomena to handle and comes with its notorious 4V: Velocity, voracity, volume, and variety. In this work, we address these issues in optimization of 5G wireless networks via the notion of proactive caching at the base stations. In particular, we investigate the gains of proactive caching in terms of backhaul offloadings and request satisfactions, while tackling the large-amount of available data for content popularity estimation. In order to estimate the content popularity, we first collect users' mobile traffic data from a Turkish telecom operator from several base stations in hours of time interval. Then, an analysis is carried out locally on a big data platformand the gains of proactive caching at the base stations are investigated via numerical simulations. It turns out that several gains are possible depending on the level of available information and storage size. For instance, with 10% of content ratings and 15.4Gbyte of storage size (87%of total catalog size), proactive caching achieves 100% of request satisfaction and offloads 98% of the backhaul when considering 16 base stations.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.334-337
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• 2003

The emission of dioxins from waste incinerators is one of the most important environmental problems today, It is known that optimization of waste incinerator controllers is a very difficult problem due to the complex nature of the dynamic environment within the incinerator. In this paper, we propose applying artificial neural networks to waste incinerator controllers. We show that artificial neural networks can project the emission of dioxins with a fair degree of accuracy.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1007-1010
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• 1999

This paper describes the recognition of totally unconstrained handwritten numerals using neural networks. Neural networks with multiple output nodes have been successfully used to classify complex handwritten numerals. The recognition system consists of the preprocessing stage to extract features using Kirsch mask and the classification stage to recognize the numerals using the fully-connected recurrent neural networks (RNN). Simulation results with the numeral database of Concordia university, Montreal, Canada, are presented. The recognition system proposed in this paper outperforms other recognition systems reported on the same database.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1991.10a
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• pp.150-154
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• 1991

As subsriber's requirements for high quality of telecom service are increased, a telecommunication network becomes complex and huge, and its management becomes an essential and an important factor in the evolution of telecommunication networks. In this paper, we focus on the network performance management and discuss the strategy of near real-time performance evaluation and control in Korea Telecome (KT) networks.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.575-578
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• 2000

The method for immittance conversion and its mathematical properties are discussed. Some design methods for complex multilayer embeddeding networks are proposed. Furthermore, as an application of multilayer embedding networks, the equivalent circuit model of a blood vessel is shown with its simulation results.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2011.11a
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• pp.49-49
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• 2011

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1612-1621
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• 2007

In this paper, we introduced our designed TDMA (Time Division Multiple Access) based MAC (Medium Access Control) protocol for Home Networks called HomeTDMA. We have implemented and tested it in a test bed using crossbow motes and TinyOS. We also have compared HomeTDMA and CSMA (Carrier Sense Multiple Access) in terms of space and time complexity, channel access time, delivery success ratio, and throughput. Based on our results, HomeTDMA has an advantage over CSMA on channel access time, throughput and delivery success ratioIn the case of complexity, HomeTDMA is more complex compared to CSMA. Thus, CSMA is more appropriate in wireless sensor networks (WSNs) where memory, energy, and throughput are important parameters to be considered. However, HomeTDMA has a natural advantage of collision free medium access and is very promising for home networks where a reliable transmission or data transfer and congestion control is highly preferred.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1315-1320
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• 2007

In this paper, we introduce a new fuzzy model called fuzzy combined polynomial neural networks, which are based on the representative fuzzy model named polynomial fuzzy model. In the design procedure of the proposed fuzzy model, the coefficients on consequent parts are estimated by using not general least square estimation algorithm that is a sort of global learning algorithm but weighted least square estimation algorithm, a sort of local learning algorithm. We are able to adopt various type of structures as the consequent part of fuzzy model when using a local learning algorithm. Among various structures, we select Polynomial Neural Networks which have nonlinear characteristic and the final result of which is a complex mathematical polynomial. The approximation ability of the proposed model can be improved using Polynomial Neural Networks as the consequent part.

• Journal of applied mathematics & informatics
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• v.30 no.5_6
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• pp.847-864
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• 2012

In recent years, using computer networks (wired and wireless networks) has been widespread in many applications. As computer networks become increasingly complex, the accompanied potential threats also grow to be more sophisticated and as such security has become one of the major concerns in them. Prevention methods alone are not sufficient to make them secure; therefore, detection should be added as another defense before an attacker can breach the system. Intrusion Detection Systems (IDSs) have become a key component in ensuring systems and networks security. An IDS monitors network activities in order to detect malicious actions performed by intruders and then initiate the appropriate countermeasures. In this paper, we present a survey and taxonomy of intrusion detection systems and then evaluate and compare them.