• Journal of the Korean Society for information Management
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• v.19 no.1
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• pp.47-69
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• 2002

The concept based retrieval model has shown a higher performance than those of the simple matching function method or the P-norm retrieval method introduced to compensate the demerits of the Boolean retrieval model. However. it takes too long to create a semantic-net knowledge base, which is essential in concept exploration. In order to solve such demerits. a method was sought out by creating a distributed knowledge base by subjects to reduce construction time without hindering the performance of retrieval.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.10a
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• pp.202-207
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• 1998

The network reliability is to be computed in terms of the terminal reliability. The computation of a terminal reliability is started with a Boolean sum of products expression corresponding to simple paths of the pair of nodes. This expression is then transformed into another equivalent expression to be a Disjoint Sum of Products form. But this computation of the terminal reliability obviously does not consider the communication between any other nodes but for the source and the sink. In this paper, we derive the overall network reliability which all other remaining nodes. For this, we propose a method to make the SOP disjoint for deriving the network reliability expression from the system success expression using the modified Sheinman's method. Our method includes the concept of spanning trees to find the system success function by the Cartesian products of vertex cutsets.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.11
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• pp.132-139
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• 1993

This paper presents a new performance-driven multi-levelizer which transforms a two-level description into a boolean network of the multilevel structure satisfied with user's costraints, such as chip area, the number of wires and literals, maximum delay, function level, fanin, fanout, etc.. The performance of circuits is estimated by reference to the informations in cell library through the cell mapping phase, and multi-levelization of circuits is constructed by the decomposition using the kernel and factoring concepts. Here, the saving cost of a common subexpression is defined to the sum of area and delay saved, when it is substituted. The experiments with MCNC benchmarks show the efficiency of the proposed method.

• Journal of Computational Design and Engineering
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• v.3 no.4
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• pp.370-384
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• 2016

Computer-aided materials design requires new modeling approaches to characterize and represent fine-grained geometric structures and material compositions at multiple scales. Recently, a dual-Rep approach was developed to model materials microstructures based on a new basis function, called surfacelet. As a combination of implicit surface and wavelets, surfacelets can efficiently identify and represent planar, cylindrical, and ellipsoidal geometries in material microstructures and describe the distribution of compositions and properties. In this paper, these primitive surfacelets are extended and composite surfacelets are proposed to model more complex geometries. Composite surfacelets are constructed by Boolean operations on the primitives. The surfacelet transform is applied to match geometric features in three-dimensional images. The composition of the material near the identified features can then be modeled. A cubic surfacelet and a v-joint surfacelet are developed to demonstrate the reverse engineering process of retrieving material compositions from material images.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.3
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• pp.150-157
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• 1996

In this paper, to develop a smart CAD/CAM system for systematically performing from the 3-D solid shape design of products to the CNC cutting operation of products by a machining center, a B-Rep solid modeler is realized based on the half edge data structure. Because the B-Rep solid modeler has the various capabilities related to the solid definition functions such as the creation operation of primitives and the translational and rotational sweep operation, the solid manipulation functions such as the split operation and the Boolean set operation, and the solid inversion function for effectively using the data structure, the 3-D solid shape of products can be easily designed and constructed. Also, besides the automatic generation of CNC code, the B-Rep solid modeler can be used as a powerful tool for realizing the automatic generation of finite elements, the interfer- ence check between solids, the structural design of machine tools and robots and so on.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.1
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• pp.1-7
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• 2007

An MTJ element not only computes Boolean function but also stores the output result in itself. We can make the most use of magneto-logic's merits by employing the magneto-logic in substitution for the sequential logic as well as the combinational logic. This unique feature opens a new horizon for potential application of MTJ as a universal logic element. Magneto-logic circuits using MTJ elements are more integrative and non-volatile. This paper presents novel 3-bit magneto-logic up/down counters and presents simulation results based on the HSPICE macro-model of MTJ that we have developed.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.5
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• pp.61-69
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• 2015

We are in overload status of information not just in a flood of information due to the data pouring from various kinds of mobile devices, online and Social Network Service(SNS) every day. While there are many existing information already created, lots of new information has been created from moment to moment. Linkage analysis has the shortcoming in that it is difficult to find the information we want since the number of rules increases geometrically as the number of item increases with the method of finding out frequent item set where the frequency of item is bigger than minimum support in this information. In this regard, this thesis proposes WT-algorithm that represents the transaction data set as Boolean variable item and grants weight to each item by making algorithm with Quine-McKluskey used to simplify the logical function. The proposed algorithm can improve efficiency of data mining by reducing the unnecessary rules due to the advantage of simplification regardless of number of items.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1652-1662
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• 1995

In this paper, a hybrid neural network is proposed to improve the learning ability of a neural network. The union of the characteristics of a Self-Organizing Neural Network model and of multi-layer perceptron model using the backpropagation learning method gives us the advantage of reduction of the learning error and the learning time. In learning process, the proposed hybrid neural network reduces the number of nodes in hidden layers to reduce the calculation time. And this proposed neural network uses the fuzzy feedback values, when it updates the responding region of each node in the hidden layer. To show the effectiveness of this proposed hybrid neural network, the boolean function(XOR, 3Bit Parity) and the solution of inverse kinematics are used. Finally, this proposed hybrid neural network is applied to the visual tracking control of a PUMA560 robot, and the result data is presented.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.453-454
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• 2006

This paper describes a processing verification technique for developing about end-milling cutters. Developed software is processing verification module for manufacturing. By using cutting simulation method, we can obtain center points of finding wheel via Boolean operation between a grinding wheel and a cylindrical workpiece. The obtained CL data can be used for calculating NC data. After then, we can simulate by using designed grinding machine and NC data. This research has been implemented on a commercial CAD system by using the API function programming. The operator can evaluate the cutting simulation process and reduce the time of design and manufacturing.