• Journal of the Korean Institute of Telematics and Electronics A
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• v.28A no.10
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• pp.847-854
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• 1991

This paper presents a new output phase assignment algorithm which determines the phases of all the nodes in a given boolean network. An estimation function is defined, which is represented by the relation between the literals in the given function expression. A weight function, WT (fi, fj) is defined, which is represented by approximate amount of common subexpression between function fi and fj. Common Subexpression Graph(CSG) is generated for phase selection by the weight function between all given functions. We propose a heuristic algorithm finding subgraph of which sum of weights has maximum by assigning phases into the given functions. The experiments with MCNC benchmarks show the efficiency of the proposed method.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.90-94
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• 1987

A structured user-friendly procedures which enable users to program in GRAFCET form directly from sequence specifications have been developed. Using these procedures, we can program the programmable logic controller (PLC) in sequential control and realize programming, debugging, and real-time monitoring. GRAFCET has many advantages like parallelism expression, so we can expect higher productivity and easier maintenance than boolean language or relay-ladder diagram specification when adapts them to PLC.

• Journal of the Korea Society of Computer and Information
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• v.20 no.11
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• pp.25-30
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• 2015

The enormous increase of data with the development of the information technology make internet users to be hard to find suitable information tailored to their needs. In the face of changing environment, the information filtering method, which provide sorted-out information to users, is becoming important. The data on the internet exists as various type. However, similarity calculation algorithm frequently used in existing collaborative filtering method is tend to be suitable to the numeric data. In addition, in the case of the categorical data, it shows the extreme similarity like Boolean Algebra. In this paper, We get the similarity in SNS user's information which consist of the mixed data using the Gower's similarity coefficient. And we suggest a method that is softer than radical expression such as 0 or 1 in categorical data. The clustering method using this algorithm can be utilized in SNS or various recommendation system.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2726-2728
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• 2001

This paper describes an optimal synthesis method of binary neural network(BNN) for an approximation problem of a circular region using a newly proposed learning algorithm[7] Our object is to minimize the number of connections and neurons in hidden layer by using a Newly Expanded and Truncated Learning Algorithm(NETLA) for the multilayer BNN. The synthesis method in the NETLA is based on the extension principle of Expanded and Truncated Learning(ETL) and is based on Expanded Sum of Product (ESP) as one of the boolean expression techniques. And it has an ability to optimize the given BNN in the binary space without any iterative training as the conventional Error Back Propagation(EBP) algorithm[6] If all the true and false patterns are only given, the connection weights and the threshold values can be immediately determined by an optimal synthesis method of the NETLA without any tedious learning. Futhermore, the number of the required neurons in hidden layer can be reduced and the fast learning of BNN can be realized. The superiority of this NETLA to other algorithms was proved by the approximation problem of one circular region.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.33-41
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• 2015

In this paper, the simplification procedure of Karnaugh Map, which is essential to design digital logic circuits, was implemented as web-based educational Java applets. The learners will be able to experience interesting learning process by executing the proposed Java applets. In addition, since the proposed Java applets were designed to contain educational technologies by step-by-step procedure, the maximization of learning efficiency can be obtained. The learners can make virtual experiments on the simplification of digital logic circuits by clicking on some buttons or filling out some text fields. Furthermore, the Boolean expression and its schematic diagram occurred in the simplification process will be displayed on the separate frame so that the learners can learn effectively. The schematic diagram enables them to check out if the logic circuit is correctly connected or not. Finally, since the simplification algorithm used in the proposed Java applet is based on the modified Quine-McCluskey minimization technique, the proposed Java applets will show more encouraging result in view of learning efficiency if it is used as assistants of the on-campus offline class.

• The Journal of Korean Association of Computer Education
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• v.20 no.4
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• pp.77-84
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• 2017

This paper proposes a tool that can be used as a logical expression simplification tool that can be used for deepening learning of logic circuits and further utilized as a design automation tool for optimizing semiconductor parts. The simplification method of logical expressions proposed in this paper is to find common subexpressions existing in various logical expressions and reduce the repetitive use. Finally, the goal is to minimize the number of literals used in all logical expressions. These previous studies failed to produce a common subexpression embedded in the logical expressions because they only use division principle. The proposed method uses cubes with a Hamming distance of 3 to find the common subexpression embedded between logical expressions. Experiments using benchmark circuits show that the proposed method reduces the number of literals by as much as 47% when comparing simplifications with other methods.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.10
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• pp.1305-1313
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• 2013

In this study, a method to apply feature-based simplification to boundary representation models is proposed. For feature-based simplification, a volume decomposition tree is created from a boundary representation model. The volume decomposition tree is represented by regularized Boolean operations of additive volumes, subtractive volumes, and fillet/round/chamfer volumes, and it is generated by stepwise volume decomposition, which consists of fillet/round/chamfer decomposition, wrap-around decomposition, volume split decomposition, and cell-based decomposition. After the volume decomposition tree is transformed to an infix expression, the CAD model can be simplified by reordering the volumes. To verify the proposed method, a prototype system was implemented, and experiments on test cases were conducted. From the results of the experiments, it is verified that the proposed method is useful for simplifying CAD models based on boundary representation.