• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.19-30
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• 2012

The context aware service is the service to provide useful information to the users by recognizing surroundings around people who receive the service via computer based on computing and communication, and by conducting self-decision. But CAS(Context Awareness System) shows the weak point of small-scale context awareness processing capacity due to restricted mobile function under the current mobile environment, memory space, and inference cost increment. In this paper, we propose a mobile cloud context system with using Google App Engine based on PaaS(Platform as a Service) in order to get context service in various mobile devices without any subordination to any specific platform. Inference design method of the proposed system makes use of knowledge-based framework with semantic inference that is presented by SWRL rule and OWL ontology and Jess with rule-based inference engine. As well as, it is intended to shorten the context service reasoning time with mapping the regular reasoning of SWRL to Jess reasoning engine by connecting the values such as Class, Property and Individual which are regular information in the form of SWRL to Jess reasoning engine via JessTab plug-in in order to overcome the demerit of queries reasoning method of SparQL in semantic search which is a previous reasoning method.

• Journal of the Korea Convergence Society
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• v.8 no.2
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• pp.27-33
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• 2017

To efficiently provide cloud computing services to users over the Internet, IT resources must be configured in the data center based on virtualization and distributed computing technology. This paper focuses specifically on the problem that new training data can be added at any time in a wide range of fields, and new attributes can be added to training data at any time. In such a case, rule generated by the training data with the former attribute set can not be used. Moreover, the rule can not be combined with the new data set(with the newly added attributes). This paper proposes further development of the new inference engine that can handle the above case naturally. Rule generated from former data set can be combined with the new data set to form the refined rule.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1509-1516
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• 2022

This paper presents a method to generate a model of the code implementation for UML state diagrams. First, it promotes the states of a state machine into objects, and then it structures the behavior model on the mechanism of a state diagram based on State design pattern. Then, it establishes the rules of generating the code implementation, and using the rules, the Java code mode is generated for the implementations of State Diagrams in Java syntax grammar. In addition, Structuring the information of the code model is necessary for generating Java code automatically. The meta information is composed of Meta-Class Model and Meta-Behavior Model, on which we could construct the automatic code generating engine for UML State Diagrams. The implementation model generation method presented in this paper could be used as a stand-alone engine, or included and integrated as a module in the UML tools.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.200-204
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• 2006

본 논문은 지식 기반 정보유통 플랫폼 OntoFrame-K$^{(R)}$ 상에서 추론을 이용하여 연구자 간 협업 서비스를 제공할 수 있도록 하는 DBMS 기반 추론 서비스 OntoThink-K$^{(R)}$에 대해 기술한다. 본 추론 서비스는 URI 서버를 이용하여 RDF 트리플을 생성하고 추론 규칙에 의해 해당 트리플을 확장하며 SPARQL을 통해 질의 결과를 생성해낸다. 특히 이 모든 과정은 DBMS 기반으로 설계 구현되었는데 URI 서버와 성과 비성과 등록 인터페이스를 통해 별도의 추론 엔진을 사용하지 않고도 정합성이 보장되는 지식을 생성 관리할 수 있도록 하며, 불안정한 성능을 보이는 추론 엔진을 이용하지 않기 때문에 안정적인 성능을 보장할 수 있다는 데 그 특징이 있다. OntoThink-K$^{(R)}$는 온톨로지 스키마 트리플, 인스턴스 트리플, 그리고 전방 추론을 통해 획득한 추가 트리플을 포함하는 확장 트리플을 기반 지식으로 하는데, 최종 사용되는 RDF 트리플의 크기는 지식 확장 이전 631,158개, 지식 확장 이후 1,112,100개이다.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.11
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• pp.235-244
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• 2017

This paper aims to design a system for psychological diagnosis in sandbox play by applying rule based expert system. Sandbox play is one of play therapy and it is a technique that can be combined with psychological diagnosis and treatment using sand and various kinds of figures. In this technique, we focus on psychological diagnostic factors and try to implement a system that automatically diagnoses psychological types when input values are given. Therefore, six kinds of language objects are set and the rules are created according to the types of figures, arrangement of figures, and production time in the sand box used as a reference element in the diagnosis method. In this system, it is assumed that the client recognizes the finished sandbox as a sensor device. Then, when the recognized state enters the input value, the rules based on the language object are ignited in order. Through this, the client is diagnosed with one of 26 types of psychology. As a result, the diagnostic process is simplified and automated. Accordingly, a more detailed psychological diagnosis and treatments are provided.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.4
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• pp.65-74
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• 2009

The risk of health impairment due to poor ventilation, fire and explosion by inflammable materials, and other unintended occurrences is always present in dangerous workplaces such as manholes, underground septic tanks, storage tanks and confined areas. Therefore, it a system which can monitor harmful working environment through sensors in workplace on a realtime basis and keep workers safe from the risk is needed. This paper has attempted to design an inference engine to monitor harmful environments in the workplace. The proposed inference engine has a rule-based system structure using JESS. This system is not confined to a particular computing platform and is easily interlocked with OSGi-based middleware.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.99-108
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• 2007

Context-Aware system using ontology is able to infer a context from help by reasoning engine. It can solve the ambiguity of intention reasoning of context-aware system as it is being made a reasoning rule followed reasoning grammar and being helped by reasoning engine, Also, it has a merit that is easy to apply to new environment by excluding reasoning algorithm from the program. In this paper, we are present context-aware system using ontology, We have tested and implemented it at home basis environment to verify of its effectiveness.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.229-236
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• 2011

In this paper we present light weighted English-to-Korean and Korean-to-English mobile translators on smart phones. For natural translation and higher translation quality, translation engines are hybridized with Translation Memory (TM) and Rule-based translation engine. In order to maximize the usability of the system, we combined an Optical Character Recognition (OCR) engine and Text-to-Speech (TTS) engine as a Front-End and Back-end of the mobile translators. With the BLEU and NIST evaluation metrics, the experimental results show our E-K and K-E mobile translation equality reach 72.4% and 77.7% of Google translators, respectively. This shows the quality of our mobile translators almost reaches the that of server-based machine translation to show its commercial usefulness.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.521-524
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• 2007

추론 기반의 온톨로지 구축은 시맨틱 웹 응용의 구현을 위한 최소 요건이다. 그러나 현재 시맨틱 웹응용에 적용된 대부분의 온톨로지들은 추론을 통한 지식의 재사용을 제공하지 못하며, 이는 시맨틱 웹응용의 발전에 많은 지장을 주는 요인이다. 따라서 본 연구는 서술 논리와 규칙 언어로 표현된 추론 기반의 웹 온톨로지를 구축하고, 이를 지능형 이미지 검색에 적용하였다. 추론 엔진을 이용한 지능형 이미지 검색 결과 실험으로, 추론 기반의 웹 온톨로지와 주석 기반의 웹 온톨로지를 이미지 검색 시스템에 적용하였으며, 추론 기반의 웹 온톨로지를 적용한 검색 결과가 재현율과 정확율에 있어 더욱 우수한 성능을 보여주었다.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.67-81
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• 2006

While the existing Web focuses on the interface with human users based on HTML, the next generation Web will focus on the interaction among software agents by using XML and XML-based standards and technologies. The inference engine, which will serve as brains of software agents in the next generation Web, should thoroughly understand the Semantic Web, the standard language of the next generation Web. As abasis for the service, the W3C (World Wide Web Consortium) has recommended SWRL (Semantic Web Rule Language) which had been made by compounding OWL (Web Ontology Language) and RuleML (Rule Markup Language). In this research, we develop a backward chaining inference engine SMART-B (SeMantic web Agent Reasoning Tools -Backward chaining inference engine), which uses SWRL and OWL to represent rules and facts respectively. We analyze the requirements for the SWRL-based backward chaining inference and design analgorithm for the backward chaining inference which reflects the traditional backward chaining inference algorithm and the requirements of the next generation Semantic Web. We also implement the backward chaining inference engine and the administrative tools for fact and rule bases into Java components to insure the independence and portability among different platforms under the environment of Ubiquitous Computing.