• Journal of KIISE:Software and Applications
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• v.36 no.2
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• pp.153-160
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• 2009

As size of ontology has been increased more and more, the descriptions in the ontologies become more complicated, Therefore finding and modifying unsatisfiable concepts is hard work in ontology construction process, Minerva is an ontology reasoner which detects unsatisfiable concepts automatically and infers subsumption relation between concepts in ontology, Most description logic based ontology reasoners (including Minerva) work using tableaux algorithm, Because tableaux algorithm is very costly, ontology reasoners need various optimization methods, In this paper, we propose optimizing methods to reduce execution time of tableaux algorithm based ontology reasoner. Proposed methods were applied to Minerva which was developed as preceding study result. In consequence the new version Minerva shows high performance.

• Journal of the Microelectronics and Packaging Society
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• v.19 no.4
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• pp.71-78
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• 2012

This paper describes trends in conventional scaling compared with advanced technologies such as 3D integration (3DI) and bumpless through-silicon via (TSV) processes, as well as the characteristics of CMOS (Complementary Metal Oxide Semiconductor) Logic device after thinning the wafers to less than $10{\mu}m$. Each module process including thinning, stacking, and TSV, is optimized for 3D Wafer-on-Wafer (WOW) application. Optimization results are discussed with valuable data in detail. Since vertical wiring of bumpless TSV can be connected directly to the upper and lower substrates by self-alignment, bumps are not necessary when TSV interconnects are used.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.53-58
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• 2002

In the construction of successful fuzzy models for nonlinear systems, the identification of an optimal fuzzy model system is an important and difficult problem. Traditionally, sGA(simple genetic algorithm) has been used to identify structures and parameters of fuzzy model because it has the ability to search the optimal solution somewhat globally. But SGA optimization process may be the reason of the premature local convergence when the appearance of the superior individual at the population evolution. Therefore, in this paper we propose a new method that can yield a successful fuzzy model using VmGA(virus messy genetic algorithms). The proposed method not only can be the countermeasure of premature convergence through the local information changed in population, but also has more effective and adaptive structure with respect to using changeable length string. In order to demonstrate the superiority and generality of the fuzzy modeling using VmGA, we finally applied the proposed fuzzy modeling methodof a complex nonlinear system.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.11
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• pp.85-95
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• 2000

FIR digital filter is one of important blocks in DSP application. For more effective operation, lots of architecture are proposed. In our paper, we proposed a high speed FIR filter with area efficiency. To fast operation, we used transposed form filter as basic architecute. And, we used dual path registers line to wupport variation of filter operation, and filter cascade is also considered. To reduce area, we adopted truncated Booth multiplier to our filter design. As a result, we showed that filter area is reduced when filter optimization using of dual path registers line and truncated multiplier with same constraints againt previous method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.3
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• pp.31-39
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• 1990

An optimization problem of AND-EXOR PLA's with input decoders can be regarded as a minimization problem of Exclusive-Or Sum-Of-Products expressions (ESOP's) for multiple-valued input two-valued output functions. In this paper, We propose a minimization algorithm for ESOP's. The algorithm is based on an iterative improvement. Five rules are used to replace a pair of products with another one. We minimized many ESOP's for arithmetic circuits. In most cases, ESOP's required fewer products than SOP's to realized same functions.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.451-458
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• 2006

The goal of many researchers in the field of structural engineering is to reduce both damage to building structures and discomfort of their inhabitants during strong motion seismic events. The present paper reports on analytical work conducted with this aim in mind as a prior research of experimental study. A four-story, 6.4 m tall, laboratory model of a building is employed as a example structure. The laboratory structure has graphite epoxy columns and each floor is equipped with a chevron brace that serves to resist inter-story drift with the installation of a magnetorheological (MR) damper. An artificial excitation has been generated with a robust range of seismic characteristics. A series of numerical simulations demonstrates that an optimized fuzzy controller is capable of robust performance for a variety of seismic base motions. Optimization of the fuzzy controller is achieved using multi-objective genetic algorithm(MOGA), i.e. NSGA-II. Multiple objective functions are used in order to reduce both peak and root-means-squared displacement and accelerations at the floor levels of the building.

• Journal of the Korean Institute of Telematics and Electronics
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• v.17 no.6
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• pp.51-57
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• 1980

Any switching function can be constructed with universal building block of MAND gate. Threelevel AND-NOT logic networks with only true inputs are called TANT networks. Systematic approach to TANT minimization starts from the UF type minterm with the smallest subscript and ends when UF type minterms are all covered. Optinal PEI is composed of CPPI or EPPi without C-C table. The algorithm in this work is usful in solving TANT optimization porblem of four or five variables by hand solution. When variable are six or more, it is required to be solved by computer, A CAD software package of this algorithm with FORTRAN IV language is made to solve such problems.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.491-501
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• 2002

Case-based reasoning is emerging as a leading methodology for the application of artificial intelligence. CBR is a reasoning methodology that exploits similar experienced solutions, in the form of past cases, to solve new problems. Hybrid model achieves some convergence of the wide proliferation of credit evaluation modeling. As a result, Hybrid model showed that proposed methodology classify more accurately than any of techniques individually do. It is confirmed that proposed methodology predicts significantly better than individual techniques and the other combining methodologies. The objective of the proposed approach is to determines a set of weighting values that can best formalize the match between the input case and the previously stored cases and integrates fuzzy sit concepts into the case indexing and retrieval process. The GA is used to search for the best set of weighting values that are able to promote the association consistency among the cases. The fitness value in this study is defined as the number of old cases whose solutions match the input cases solution. In order to obtain the fitness value, many procedures have to be executed beforehand. Also this study tries to transform financial values into category ones using fuzzy logic approach fur performance of credit evaluation. Fuzzy set theory allows numerical features to be converted into fuzzy terms to simplify the matching process, and allows greater flexibility in the retrieval of candidate cases. Our proposed model is to apply an intelligent system for bankruptcy prediction.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.1-6
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• 2007

The SVDD (support vector data description) is one of the most well-known one-class support vector learning methods, in which one tries the strategy of utilizing balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects. Recently, with the objective of generalizing the SVDD which treats all training data with equal importance, the so-called D-SVDD (density-induced support vector data description) was proposed incorporating the idea that the data in a higher density region are more significant than those in a lower density region. In this paper, we consider the problem of further improving the D-SVDD toward the use of a partial reference set for testing, and propose an LMI (linear matrix inequality)-based optimization approach to solve the improved version of the D-SVDD problems. Our approach utilizes a new class of density-induced distance measures based on the RSDE (reduced set density estimator) along with the LMI-based mathematical formulation in the form of the SDP (semi-definite programming) problems, which can be efficiently solved by interior point methods. The validity of the proposed approach is illustrated via numerical experiments using real data sets.

• Journal of KIISE:Software and Applications
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• v.34 no.6
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• pp.530-538
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• 2007

Most existing deductive engines study for optimization of TBox based on Tableaux algorithm. However, in order to deduce mass-storing ABox in reality, it can't be decided in finite time. Therefore, for the efficiency of the deductive engine, there needs to be reasoning technique optimized for ABox. This paper uses the method that changes OWL-DL based Ontology to the form of Rule like Datalog in order to interlock store device such as RDBMS. Ultimately, it tries to in circumstance of real world. Therefor, using Axiom that OWL holds, it suggests reasoning method that applies rules including datatype.