• Journal of KIISE:Computing Practices and Letters
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• v.12 no.6
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• pp.379-385
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• 2006

To improve reusability and adaptation of variable components, rule-based component development has been used. Rule engines usually need additional script languages for rule expression and have difficulty in expressing complex business rules. In this paper, we propose a compiler-based rule engine for rich rule expression and improving performance. This rule engine uses Java programming language to express conditions and action parts of rules and that it can easily express complex business rules. It creates and executes condition and action objects at run time. In view of Performance, the rule engine is better than a script based rule engine. According to our experiments, our compiler-based nile engine shows 2.5 times better performance that script-based JSR 94 rule engine.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.852-855
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• 2010

Tree type of Rule Case will be processed by the method that provide practical Rule Case to Rule Engine that is made with procedural language beforehand, then the Rule Engine according to the condition of the special Rule Case to return result in current Rule-Based System. There are two disadvantages in the method; the first is according to specific business rule after construct the Rule Engine when the business rule changing the Rule Engine also must be changed. The second is when Rule have many conditions the Rule Engine will become very complex and the speed of processing Rule Case will become very slow. In this paper, we will propose a simplified algorithm that according to the theory of ID Tree to produce Rules which be used in Rule-Based System. The algorithm can not only produce Rules but also make sure of satisfying change of business rule by execute the algorithm. Because it is not necessary to make a Rule Engine, we will anticipate effect of increasing speed and reducing cost from Rule-Based System of applying the algorithm.

• Proceedings of the Korea Society for Simulation Conference
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• 2003.11a
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• pp.51-57
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• 2003

In operating distributed systems, proactive management is one of the major concerns for better quality of service and future capacity planning. In order to handle this management problem effectively, it is necessary to analyze performances of the distributed system and events generated by components in the system. This paper provides a rule-based event parsing engine for proactive management. Our event parsing engine uses object hooking-based and event-token approaches. The object hooking-based approach prepares new conditions and actions in Java classes and allows dynamically exchange them as hook objects in run time. The event-token approach allows the event parsing engine consider a proper sequence and relationship among events as an event token to trigger an action. We analyze the performance of our event parsing engine with two different implementations of rule structure; one is table-based and the other is tree-based.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.2
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• pp.59-68
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• 2016

Context-aware services recognize the context of situation environments of users and provide useful services according to the context for users. Usual rule-based systems can be used for context-aware services with the specified rules that express context information and operations. This paper proposes a light-weight rule engine that minimizes memory consumption for resource-constrained smart things. The rule engine manages rules at the minimum condition level, removes memories for intermediate rule matching results, and uses hash tables to store rules and context information efficiently. The implemented engine is verified using a rule set of a mouse training system and experiment results shows the engines consumes very little memory compared to the existing Rete algorithm with some sacrifice of execution time.

• ETRI Journal
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• v.29 no.4
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• pp.477-488
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• 2007

In recent years, numerous studies have identified and explored issues related to web-service-oriented business process specifications, such as business process execution language (BPEL). In particular, business rules are an important cross-cutting concern that should be distinguished from business process instances. In this paper, we present a rule-based aspect oriented programming (AOP) framework where business rule aspects contained in business processes can be effectively separated and executed. This is achieved by using a mechanism of the business rule itself at the business rule engine instead of using existing programming language-based AOP technologies. Through some illustrative examples, this work also introduces a method by which business rule aspects, separated through an external rule engine, can be represented and evaluated. We also demonstrate how they can be dynamically woven and executed by providing an implementation example which uses two open-source-based products, the Mandarax rules engine and Bexee BPEL engine.

• The KIPS Transactions:PartD
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• v.17D no.6
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• pp.405-414
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• 2010

A rule is defined as a case to determine the target values according to combination of various Business factors. The information system is used to represent enterprise's business, which includes and implements the amount of these rules to Rule-Based System. A Rule-Based System can be constructed by using the rules engine method or Relational Database technology. Because the rules engine method has some disadvantages, the Rule-Based System is mostly developed with Relational Database technology. When business scales become larger and more complex, a large number of various rule cases must be operated in system, and processing these rule cases requires additional time, overhead and storage space, and the speed of execution slows down. To solve these problems, we propose a simplification algorithm that converts a large amount of rule cases to simplification rule cases with same effects. The proposed algorithm is applied to hypothetical business rule data and a large number of simplification experiments and tests are conducted. The final results proved that the number of rows can be reduced to some extent. The proposed algorithm can be used to simplify business rule data for improving performance of the Rule-Based System implemented with the Relational Database.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.89-94
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• 2010

The most important of rule-base system is the knowledge base that determines the power of rule-base system. The important form of this knowledge is how to descript kinds of rules. The Rule-Base System (RBS) has been using in many field that need reflect quickly change of business rules in management system. As far, when develop the Rule-Based System, we must make a rule engine with a general language. There are three disadvantage of in this developed method. First, while there are many data that must be processed in the system, the speed of processing data will become very slow so that we cannot accept it. Second, we cannot change the current system to make it adaptive to changes of business rules as quickly as possible. Third, large data make the rule engine become very complex. Therefore, in this paper, we propose the two important methods of raising efficiency of Rule-Base System. The first method refers to using the Relational database technology to process the rules of the Rule-Base System, the second method refers to a algorithm of according to Quine McCluskey formula compress the rows of rule table. Because the expressive languages of rule are still remaining many problems, we will introduce a new expressive language, which is Rule-Base Data Model short as RBDM in this paper.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.1
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• pp.42-48
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• 2003

In general many engineers can diagnose the fault condition using the abnormal ones among data monitored from a diesel engine, but they don't need the system modelling or identification for the work. They check the abnormal data and the relationship and then catch the fault condition of the engine. This paper proposes the construction of a fault diagnosis engine through malfunction data gained from the data fault detection system of neural networks for diesel generator engine, and the rule inference method to induce the rule for fuzzy inference from the malfunction data of diesel engine like a site engineer with a fuzzy system. The proposed fault diagnosis system is constructed in the sense of the Malfunction Diagnosis Engine(MDE) and Hierarchy of Malfunction Hypotheses(HMH). The system is concerned with the rule reduction method of knowledge base for related data among the various interactive data.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.4
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• pp.379-387
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• 2018

In order to make the IoT ecosystem more usable and friendly to general users, the interaction between the users and platforms/devices and its UX must be improved. In this study, a web-based rule engine system to help users intuitively interact with the various devices and services in IoE (Internet of Everything) platform is proposed. The proposed system consists of web interfaces and UI components for creating and managing rule-based scenarios using sensors, actuators, and external services in an intuitive way. Also, a rule management module for automatically translating the rules from the web interface into Nools rule engine compatible ones is proposed. Finally, we show the usability and feasibility of the proposed system by demonstration of rule-based use cases of IoT devices and external services.

• 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.