• Journal of Bio-Environment Control
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• v.12 no.1
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• pp.30-37
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• 2003

An expert system was developed for the stress diagnosis of cucumber and tomato using FoxPro. The principle points in building the system were integration with Korean, effective processing of mass information, and easy access for non-experts such as farmers. The method of inferencing was forward chaining based on pattern matching. Knowledge base was expressed with IF∼THEN rules and was expressed in the form of tree. Also, the expert system was designed so that additions and modifications of all information could easily be performed on windows. The results tested by farmers with the developed system showed that the expert system was reliable for the practical use. It was expected the expert system could be directly applied to the stress diagnosis of other vegetable plants by modifying only data bases.

• Journal of Internet Computing and Services
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• v.13 no.3
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• pp.115-126
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• 2012

Mashups have become very popular over the last few years, and their use also varies for IT convergency services. In spite of their popularity, there are several challenging issues when combining Open APIs into mashups, First, since portal sites may have a large number of APIs available for mashups, manually searching and finding compatible APIs can be a tedious and time-consuming task. Second, none of the existing portal sites provides a way to leverage semantic techniques that have been developed to assist users in locating and integrating APIs like those seen in traditional SOAP-based web services. Third, although suitable APIs have been discovered, the integration of these APIs is required for in-depth programming knowledge. To solve these issues, we first show that existing techniques and algorithms used for finding and matching SOAP-based web services can be reused, with only minor changes. Next, we show how the characteristics of APIs can be syntactically defined and semantically described, and how to use the syntactic and semantic descriptions to aid the easy discovery and composition of Open APIs. Finally, we propose a goal-directed interactive approach for the dynamic composition of APIs, where the final mashup is gradually generated by a forward chaining of APIs. At each step, a new API is added to the composition.

• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.205-227
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• 2002

Our study is focused on a multiple-agent system to provide efficient collaborative work by automating the conference calling process with the help of intelligent agents. Automating the meeting scheduling requires a careful consideration of the individual official schedule as well as the privacy and personal preferences. Therefore, the automation of conference calling needs the distributed processing task where a separate calendar management process is associated for increasing the reliability and inherent parallelism. This paper describes in detail the design and implementation issues of a multiple-agent system for conference calling that allows the convener and participants to minimize their efforts in creating a meeting. Our system is based on the client-sewer model. In the sewer side, a scheduling agent, a negotiating agent, a personal information managing agent, a group information managing agent, a session managing agent, and a coordinating agent are operating. In the client side, an interface agent, a media agent, and a collaborating agent are operating. Agents use a standardized knowledge manipulation language to communicate amongst themselves. Communicating through a standardized knowledge manipulation language allows the system to overcome heterogeneity which is one of the most important problems in communication among agents for distributed collaborative computing. The agents of our system propose the dates on which as many participants as possible are available to attend the conference using the forward chaining algorithm and the back propagation network algorithm.