• Korean Institute of Interior Design Journal
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• no.38
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• pp.258-265
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• 2003

The design of space, which focuses on human senses and perception, has become more prominent. It can be understood as the space needed for a field of experience. Phenomenological attitude focuses on the relations between human in the context of their environment. The experiences generated were used as a method of design. The method guides a formation of active space through phenomenological experience in interior space as well as architecture. To stimulate a phenomenological sensitive experience, the parameters for certain experiences were connected to the five senses, finally creating a concrete space. Water, light, air, vapor, and earth as architectural media are connected to the five senses and lead to intermediation from abstract to actual. In particular, water is deeply rooted in peoples subconsciousness and stimulates our instincts. Using water by effectively combining its symbols and physical characteristics will be a method to reinforce the experience with a given space. This study will examine the need for space experience and characteristics of water as an essential elements for perception experience and present possible experimental design.

• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1689-1699
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• 2006

A nonlinear channel blind equalizer by using a hybrid genetic algorithm, which merges a genetic algorithm with simulated annealing, and a RBF network is presented. In this study, a hybrid genetic algorithm is used to estimate the output states of a nonlinear channel, based on the Bayesian likelihood fitness function, instead of the channel parameters. From these estimated output states, the desired channel states of the nonlinear channel are derived and placed at the center of a RBF equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a conventional genetic algorithm(GA) and a simplex GA, and the relatively high accuracy and fast convergence of the method are achieved.

• Korean Journal of Computational Design and Engineering
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• v.6 no.2
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• pp.133-139
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• 2001

Since a great number of 2D engineering drawings are being used in industry and at the same time 3D CAD becomes popular in recent years, we need to reconstruct 3D CAD models from 2D legacy drawings. In this thesis, a combination of a feature recognition method and an expert system is suggested for the 3D solid model reconstruction. Modeling primitives of 3D CAD systems are recognized and constructed by using the pattern matching technique of the features modeling. Additional information for the 3D model reconstruction can be generated by extracting symbols or text entities which are related to form entities. For complex and indefinite cases which cannot be solved by the process of feature recognition, an expert system with a rule base has been used for decision-making. A 3D reconstruction system which recognizes 2D DXF drawing files has been implemented where models composed with protrusions, holes, and cutouts can be handled.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.259-265
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• 2004

In this study, a hybrid genetic algorithm merged with simulated annealing is presented to solve nonlinear channel blind equalization problems. The equalization of nonlinear channels is more complicated one, but it is of more practical use in real world environments. The proposed hybrid genetic algorithm with simulated annealing is used to estimate the output states of nonlinear channel, based on the Bayesian likelihood fitness function, instead of the channel parameters. By using the desired channel states derived from these estimated output states of the nonlinear channel, the Bayesian equalizer is implemented to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a conventional genetic algorithm(GA) and a simplex GA. In particular, we observe a relatively high accuracy and fast convergence of the method.

• Journal of information and communication convergence engineering
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• v.5 no.1
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• pp.35-41
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• 2007

In this paper, a modified Fuzzy C-Means (MFCM) algorithm is presented for nonlinear blind channel equalization. The proposed MFCM searches the optimal channel output states of a nonlinear channel, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. In its searching procedure, all of the possible desired channel states are constructed with the elements of estimated channel output states. The desired state with the maximum Bayesian fitness is selected and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

• Journal of Mechanical Science and Technology
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• v.19 no.6
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• pp.1268-1279
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• 2005

The current method for pavement sign marking operations is labor-intensive and very dangerous due to the exposure of workers to passing traffic. It also requires blocking traffic for a long period of time resulting serious traffic jam. This paper deals with the development of a robotic system for automating the pavement sign painting operations. The robotic system consists of gantry frame equipped with transverse drive rail and automatic paint spray system. The workspace of the gantry robot is extended to one-lane width with the transverse rail system. This research also includes the development of font data structures that contain the shape information of pavement signs, such as Korean letters, English letters and symbols. The robot path is generated with this font data through the procedures of scaling up/down and partitioning the signs to be painted depending on the workspace size.

• Journal of Korea Multimedia Society
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• v.10 no.10
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• pp.1284-1294
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• 2007

In this paper, a blind nonlinear channel equalization is implemented by using a Modified Fuzzy C-Means (MFCM) algorithm. The proposed MFCM searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.382-388
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• 2007

In this paper, a modified Fuzzy C-Means (MFCM) algorithm is presented for nonlinear blind channel equalization. The proposed MFCM searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6A
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• pp.500-505
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• 2009

In this paper, We present a low complexity candidate list generation scheme in iterative MIMO receiver. Since QAM modulation can be decomposed into HP symbols and LP symbol and HP symbol is robust in error capability, we generate HP symbol list with simple ZF detector output and its corresponding neighbor HP symbols, Then, based on HP symbol list, the LP symbol list is generated by using the sphere decoder. From the second iteration, since apriori value from channel decoder is available, the candidate list is updated based on demodulated apriori value. Through the simulation, we observe that at the first iteration, the BER performance is worse than LSD. However, as the number of iteration is increased, the proposed scheme has almost same performance as LSD. Moreover, the proposed one has reduced candidate list generation time and lower number of candidate list compared with LSD.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.1
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• pp.84-89
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• 2011

Musical sheet recognition is an emerging area as the role of computers in music increases. Although there are several well-known programs for composition, they have a limitation in that they cannot edit or play music generated from other programs. In this paper, we propose an algorithm that can read, recognize, and play music using printed sheets. The proposed algorithm first removes lines using horizontal histogram and extracts symbols. The symbols belong to one of the three categories; notes, rests, and other signs. Notes are recognized using the context information and rests and signs are recognized using a fuzzy ART algorithm. The proposed algorithm were applied to 50 pages of musical sheets and the experimental results showed that it is effective in automatic recognition of musical sheets.