• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3113-3118
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• 2000

A framework proposed in this paper includes representations of multi-objectives rule-basd constraint satisfaction problem(RCSP) and especially, flexible structure of RCSP which provides adequate solution sithin an expectation time and adaptively considers some change of constratraints on the RCSP. In this study, the power system implemented by above framework is entirely programmed by using a modeling system for the quantitative model and a rule-based constraint programming tool for the qualitative model. The results of an exemplary cse show how the structure that involves the problem representation gives the scheduler an effective decision and what are the advantages of the easy and diverse representation for considering the techmical characteristics of the units on the RCSP over the traditional problem.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.282-296
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• 2010

OWL is an ontology language for the Semantic Web, and suited to modelling the knowledge of a specific domain in the real-world. Ontology also can infer new implicit knowledge from the explicit knowledge. However, the modeled knowledge cannot be complete as the whole of the common-sense of the human cannot be represented totally. Ontology do not concern handling nonmonotonic reasoning to detect incomplete modeling such as the integrity constraints and exceptions. A default rule can handle the exception about a specific class in ontology. Integrity constraint can be clear that restrictions on class define which and how many relationships the instances of that class must hold. In this paper, we propose a practical reasoning system for open and closed-world reasoning that supports a novel hybrid integration of ontology based on open world assumption (OWA) and non-monotonic rule based on closed-world assumption (CWA). The system utilizes a method to solve the problem which occurs when dealing with the incomplete knowledge under the OWA. The method uses the answer set programming (ASP) to find a solution. ASP is a logic-program, which can be seen as the computational embodiment of non-monotonic reasoning, and enables a query based on CWA to knowledge base (KB) of description logic. Our system not only finds practical cases from examples by the Protege, which require non-monotonic reasoning, but also estimates novel reasoning results for the cases based on KB which realizes a transparent integration of rules and ontologies supported by some well-known projects.

• The Transactions of the Korea Information Processing Society
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• v.1 no.1
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• pp.114-128
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• 1994

It is very difficult for a nonprofessional programmer in Koera to write a program with very High Level Language such as, V,REFINE, GIST, and SETL, because the semantic primitives of these languages are based on predicate calculus, set, mapping, or testricted natural language. And it takes time to be familiar with these language. In this paper, we suggest a method to reduce such difficulties by programming with the declarative, procedural constructs, and aggregate constructs. And we design and implement an experimental knowledge-based automatic programming system. called HAPS(Hangul Automatic Program System). HAPS, whose input is specification such as Hangul abstract algorithm and datatype or Hangul procedural constructs, and whose output is C program. The method of operation is based on rule-based and program transformation technique, and the problem transformation technique. The problem area is general problem. The control structure of HAPS accepts the program specification, transforms this specification according to the proper rule in the rule-base, and stores the transformed program specification on the global data base. HAPS repeats these procedures until the target C program is fully constructed.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.42-52
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• 2002

Information extraction(IE) is a process of recognizing and fetching particular information fragments from a document. In previous work, most IE systems generate the extraction rules called the wrappers manually, and although this manual wrapper generation may achieve more correct extraction, it reveals some problems in flexibility, extensibility, and efficiency. Some other researches that employ automatic ways of generating wrappers are also experiencing difficulties in acquiring and representing useful domain knowledge and in coping with the structural heterogeneity among different information sources, and as a result, the real-world information sources with complex document structures could not be correctly analyzed. In order to resolve these problems, this paper presents an agent-based information extraction system named XTROS that exploits the domain knowledge to learn from documents in a semi-structured information source. This system generates a wrapper for each information source automatically and performs information extraction and information integration by applying this wrapper to the corresponding source. In XTROS, both the domain knowledge and the wrapper are represented as XML-type documents. The wrapper generation algorithm first recognizes the meaning of each logical line of a sample document by using the domain knowledge, and then finds the most frequent pattern from the sequence of semantic representations of the logical lines. Eventually, the location and the structure of this pattern represented by an XML document becomes the wrapper. By testing XTROS on several real-estate information sites, we claim that it creates the correct wrappers for most Web sources and consequently facilitates effective information extraction and integration for heterogeneous and complex information sources.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.10
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• pp.107-115
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• 1998

A multiplier bit-pair recoding technique derived from Booth algorithm is used as an effective method that can carry out a fast binary multiplication regardless of a sign of both multiplicand and multiplier. In this paper, we propose an implementation of an optical high-speed multiplier which consists of a symbolic substitution adder and an optical multiplication algorithm, which transforms and enhances the multiplier bit-pair recoding algorithm to be fit for optical characteristics. Specially, a symbolic substitution addition rules are coded with a dual-rail logic, and so the complement of the logic of the symbolic substitution adder is easily obtained with a shift operation because it is always present. We also construct the symbolic substitution system which makes superposition image by superimposing two shifted images in a serial connection and recognizes a reference image by feeding this superimposed image to a mask. Thus, the optical multiplier, which is compared with a typical system, is implemented to the smaller system by reducing the number of optical passive elements and the size of this system.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2485-2492
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• 1997

Nowadays the traffic conditions have been getting worse due to continuous increase in the number of vehicles. So it has become more important to manage traffic signal lights efficiently. Recently fuzzy logic is introduced to control the cycle time of traffic lights adaptively. Conventional fuzzy logic controller adjusts the extension time of current green phase by using the fuzzy input variables such as the number of entering vehicles at the green light and the number of waiting vehicle during the red light. However this scheme is inadequate for an intersection with variable traffic densities. In this paper, a new FLC with asymmetric membership functions that reflects more exactly traffic flows than other FLCs with symmetric ones regardless of few control rules is propsed. The effectiveness of the proposed method was shown through simulation of a single intersection. The experimental results yielded the superior performance of the proposed FLC in terms of the average delay time, the number of passed vehicles, and the degree of saturation.

• Journal of the Korea Computer Industry Society
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• v.3 no.1
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• pp.57-66
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• 2002

In this study, Multi-Values Logic processor was designed using the basic circuit of the electric current mode CMOS. First of all, binary FFT(Fast Fourier Transform) was extended and high-speed Multi-Valued Logic processor was constructed using a multi-valued logic circuit. Compared with the existing two-valued FFT, the FFT operation can reduce the number of transistors significantly and show the simplicity of the circuit. Moreover, for the construction of amount was used inside the FFT circuit with the set of redundant numbers like ［0,1,2,3］. As a result, the defects in lines were reduced and it turned out to be effective in the aspect of normality an regularity when it was used designing VLSI(Very Large Scale Integration). To multiply FFT, the time and size of the operation was used as LUT(Look Up Table) Finally, for the compatibility with the binary system, multiple-valued hybrid-type FFT processor was proposed and designed using binary-four valued encoder, four-binary valued decoder, and the electric current mode CMOS circuit.

• Journal of KIISE
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• v.41 no.10
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• pp.762-773
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• 2014

As the web of data is increasingly producing large RDFS datasets, it becomes essential in building scalable reasoning engines over large triples. There have been many researches used expensive distributed framework, such as Hadoop, to reason over large RDFS triples. However, in many cases we are required to handle millions of triples. In such cases, it is not necessary to deploy expensive distributed systems because logic program based reasoners in a single machine can produce similar reasoning performances with that of distributed reasoner using Hadoop. In this paper, we propose a scalable RDFS reasoner using logical programming methods in a single machine and compare our empirical results with that of distributed systems. We show that our logic programming based reasoner using a single machine performs as similar as expensive distributed reasoner does up to 200 million RDFS triples. In addition, we designed a meta data structure by decomposing the ontology triples into separate sectors. Instead of loading all the triples into a single model, we selected an appropriate subset of the triples for each ontology reasoning rule. Unification makes it easy to handle conjunctive queries for RDFS schema reasoning, therefore, we have designed and implemented RDFS axioms using logic programming unifications and efficient conjunctive query handling mechanisms. The throughputs of our approach reached to 166K Triples/sec over LUBM1500 with 200 million triples. It is comparable to that of WebPIE, distributed reasoner using Hadoop and Map Reduce, which performs 185K Triples/sec. We show that it is unnecessary to use the distributed system up to 200 million triples and the performance of logic programming based reasoner in a single machine becomes comparable with that of expensive distributed reasoner which employs Hadoop framework.

• Journal of Internet Computing and Services
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• v.8 no.6
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• pp.135-144
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• 2007

Feature models are widely used in domain engineering phase of software product lines development to model the common and variable concepts among products. From the feature model, the feature configurations are generated by selecting the features to be included in target product. The feature configuration represents the requirements for the specific product to be implemented. Although there are a lot of researches on how to build and use the feature models and feature configurations, the researches on the formal semantics and reasoning of them are rather inactive. This paper proposes the feature configuration verification approach based on JESS, java-based rule-base system. The Graph Product Line, a standard problem for evaluating the software product line technologies, is used throughout the paper to illustrate this approach. The approach in this paper has advantage of presenting the exact reason causing inconsistency in the feature configuration. In addition, this approach should be easily applied into other software product lines development environments because JESS system can be easily integrated with Java language.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.9
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• pp.49-57
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• 1999

The fusion of fuzzy set theory and neural networks technologies have concentrated on applying neural networks to obtain the optimal rule bases of fuzzy logic system. Unfortunately, this is very hard to achieve due to limited learning capabilities of neural networks. To overcome this difficulty, we propose a new approach in which rough set theory and neuro-fuzzy fusion are combined to obtain the optimal rule base from input/output data. Compared with conventional FNN, the proposed algorithm is considerably more realistic because it reduces overlapped data when construction a rule base. This results are applied to the construction of inference rules for controlling the temperature at specified points in a refrigerator.