• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.142-146
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• 1994

This paper proposes an fill-factor algorithm that determines embedding parameters which are needed in optimal attractor reconstruction. For reliability test, using this algorithm, we reconstructs the attractor of numerical chaotic data such as Duffing equation, Lorenz equation and Rossler equation whose embedding parameters are known. Also we reconstructs the attractor of experimental data and evaluates correlation dimension. Experimental data used in this paper are 38 ECG data of AHA(American Heart Association) ECG database. For numerical chaotic data, correlation dimension and Lyapunov exponent of reconstructed attractor are very close to those of attractor using original coordinate system.

• Journal of applied mathematics & informatics
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• v.27 no.5_6
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• pp.1331-1342
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• 2009

In this paper, we analyze the behavior of the state transition of nongroup CA with a single attractor over GF($2^p$)(p > 1), and propose the algorithm for the construction of the state transition diagram of a Single Attractor CA(SACA) over GF($2^p$) which is very different from the construction algorithm for the state transition diagram of GF(2) SACA.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.3
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• pp.315-320
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• 2010

Classifying multi-class pattern plays an important role in grouping of records in database systems, detection of faults in the VLSI circuits and so on. In this paper, we propose an algorithm for the construction of multi-class pattern classifier with minimum memory capacity using MACA(Multiple Attractor Cellular Automata) and the subspace concept for given multi-class patterns.

• KIEE International Transactions on Power Engineering
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• v.4A no.1
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• pp.33-41
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• 2004

Knowledge of partial discharge (PD) is important to accurately diagnose and predict the condition of insulation. The PD phenomenon is highly complex and seems to be random in its occurrence. This paper indicates the possible use of chaos theory for the recognition and distinction concerning PD signals. Chaos refers to a state where the predictive abilities of a systems future are lost and the system is rendered aperiodic. The analysis of PD using deterministic chaos comprises of the study of the basic system dynamics of the PD phenomenon. This involves the construction of the PD attractor in state space. The simulation results show that the variance of an orthogonal axis in an attractor of chaos theory increases according to the magnitude and the number of PDs. However, it is difficult to clearly identify the characteristics of the PDs. Thus, we calculated the magnitude on an orthogonal axis in an attractor using singular value decomposition (SVD) and principal component analysis (PCA) to extract the numerical characteristics. In this paper, we proposed the condition monitoring method for gas insulated switchgear (GIS) using SVD for efficient calculation of the variance. Thousands of simulations have proven the accuracy and effectiveness of the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1047-1054
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• 2004

One of the fundamental problems in computer science is how to store information so that it can be searched and retrieved efficiently. Hashing is a technique which solves this problem. In this paper, we propose a tree construction algorithm using linear two-predecessor single attractor cellular automata C and its complemented cellular automata. Also by using the concept of MRT we give a perfect hasing algorithm based on C.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2142-2161
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• 2018

Distance dynamics model is an excellent model for uncovering the community structure of a complex network. However, the model has poor robustness. To improve the robustness, we design an enhanced distance dynamics model based on Ego-Leader and propose a corresponding community detection algorithm, called E-Attractor. The main contributions of E-Attractor are as follows. First, to get rid of sensitive parameter ${\lambda}$, Ego-Leader is introduced into the distance dynamics model to determine the influence of an exclusive neighbor on the distance. Second, based on top-k Ego-Leader, we design an enhanced distance dynamics model. In contrast to the traditional model, enhanced model has better robustness for all networks. Extensive experiments show that E-Attractor has good performance relative to several state-of-the-art algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5276-5298
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• 2019

Internet of Things (IoT) based sensor networks have gained unprecedented popularity in recent years. With the exponential explosion of the objects (sensors and mobiles), the bandwidth and the speed of data transmission are dwarfed by the anticipated emergence of IoT. In this paper, we propose a novel heterogeneous IoT model integrated the power line communication (PLC) and WiFi network to increase the network capacity and cope with the rapid growth of the objects. We firstly propose the mean transmission delay calculation algorithm based the 3D Markov chain according to the multi-priority of the objects. Then, the attractor selection algorithm, which is based on the adaptive behavior of the biological system, is exploited. The combined the 3D Markov chain and the attractor selection model, named MASM, can select the optimal path adaptively in the heterogeneous IoT according to the environment. Furthermore, we verify that the MASM improves the transmission efficiency and reduce the transmission delay effectively. The simulation results show that the MASM is stable to changes in the environment and more applicable for the heterogeneous IoT, compared with the other algorithms.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2002.11a
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• pp.613-618
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• 2002

본 논문에서는 선형 TPMACA와 TPSACA의 특성을 이용하여 만들어진 트리구성알고리즘을 구성하고, TPSACA를 기반으로 하는 완전 해싱 알고리즘을 생성하고자 한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.5
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• pp.931-936
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• 2009

Classification problem plays a major role in grouping of the records in database systems, detection of faults in VLSI circuits, image processing, and so on. In this paper, we propose the algorithm constructing D1-MACA as a two-class classifier with minimum memory for given pattern sets using the concepts of subspace. Also we analyze the condition that is designed a two-class classifier D1-MACA with two attractors.

• Korean Institute of Interior Design Journal
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• v.27 no.2
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• pp.175-185
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• 2018

The purpose of this study is to analyze the concept of 'Gradual Differentiation' in parametric design in terms of pure model logic and thus describe the distinctive feature from the previous design method. To meet the purpose, it explores external cases like gradual factor identified in natural phenomenon and artworks and define the inherent model principles into "Self-similarity', "Correlation', and 'Temporality' by examining these features in terms of algorithm. Meanwhile, it identified the principle of gradual model representation in parametric design within a single system called 'Attractor System' by applying these three concepts into specific methods of parametric design, and by interpreting the logical structure through the association among 'Attractor', 'Field', and 'Differentiation'. The creative utilization of parameter shows that gradual model process in parametric design does not mean a passive "conversion process" merely replacing natural parameter with algorithm; rather, it refers to an active "generating process" creating new meanings and value. By continuing this process of conceptual understanding and insight, creative perspective and practical ability to interpret parameter can be improved.