Artificial intelligence integration

Artificial intelligence integration of materials evaluation functional requirements, 42,43/44 importance of implementation of technology, 42,44... 

It is this integrative attitude that today characterizes most of the work in the area of intelligent systems for process engineering, as the editors of this volume have indicated in a recent review article. (4) It is this need for integrative approaches that has moved the applications of artificial intelligence into the mainstream of engineering activities. This is certainly the pivotal feature that characterizes the ten paradigms discussed in the subsequent chapters. 

Jarke, M., Nissen, H.W., Pohl, K. Tool integration in evolving information systems environments. In Proceedings of the 3 GI Workshop Information Systems and Artificial Intelligence Administration and Processing of Complex Structures (1994)... 

Storrie, H. Semantics and verification of data flow in UML 2.0 activities. Electronic Notes in Theoretical Computer Science 127(4), 35-52 (2005) Stuckenschmidt, H., Klein, M. Integrity and change in modular ontologies. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI O3), Acapulco, Mexico, pp. 900-905. Morgan Kaufmann, San Francisco (2003)... 

C Undey, E Tatara, and A Cinar. Real-time batch process supervision by integrated knowledge-based systems and multivariate statistical methods. Engg. App. Artificial Intelligence, 16 555-566, 2003. 

Friedman M, Levy A, Millstein T (1999) Navigational plans for data integration. In Proceedings of the national conference on artificial intelligence (AAAI). American Association for Artificial Intelligence, CA, pp 67-73... 

This paper describes one of these systems called IQAP, an Intelligent Quality Assurance Planner. The needs of the OSC are discussed first and how IQAP is designed to address a specific need in the integrated OSC support system. The next section describes the system inputs and outputs, respectively. Finally, there is a discussion of how Artificial Intelligence (AI) techniques will be used to embed the expertise of experienced OSCs, field and lab personnel, and QA personnel in the development IQAP. 

These markets for chemical and biosensors will also drive further refinements and improvements in sensor design and performance. Within the next decade, chemical and biosensor fabrication and mass production will become as reliable and cost efficient as cunent production of physical sensors and will result in products which are faster responding, smaller, simpler to use, durable, and relatively inexpensive. With the addition of artificial intelligence and integration into more complex software systems, chemical and biosensors will also become smarter with capabilities applicable to almost any sensing and measurement need. 

---