Applied Information Science, Engineering and Technology: by Csilla Csendes, Sándor Fegyverneki (auth.), Gabriella

By Csilla Csendes, Sándor Fegyverneki (auth.), Gabriella Bognár, Tibor Tóth (eds.)

The goal of the booklet is to offer a range from the papers, which summarize a number of vital effects received in the framework of the József Hatvany Doctoral tuition working on the college of Miskolc, Hungary. in keeping with the 3 major learn components of the Doctoral tuition tested for info technology, Engineering and expertise, the papers could be categorised into 3 teams. they're as follows: (1) utilized Computational technological know-how; (2) creation details Engineering (IT for production included); (3) fabric movement platforms and IT for Logistics. As regards the 1st region, a few papers take care of distinctive problems with algorithms conception and its functions, with computing algorithms for engineering initiatives, in addition to yes problems with information base structures and data in depth structures. on the topic of the second one learn sector, the point of interest is on construction details Engineering with exact regard to discrete creation approaches. within the moment examine sector the papers express a few new built-in platforms compatible for optimizing discrete construction methods in a top-down manner. The papers connecting with the 3rd examine box take care of various problems with fabrics movement structures and logistics, making an allowance for of utilized mathematical types and IT-tools. The e-book makes an attempt to make sure definite equilibrium among idea and perform and to teach a few new technique either from theoretical modelling element, in addition to experimental and useful viewpoint.

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4 Optimization in Function Mapping The difficulty of function mapping is caused by ambiguous mapping between sentence analysis and function signatures (FS). This can occur when there are concepts in the domain that can fit into many FS, predicates are not assigned to an individual FS, there are missing parameters in the sentence, and similar problems arise that make mapping much harder. A mapping between a sentence analysis tree and FS can be defined as: (14) S → f i |F = { f i }, where S is the sentence analysis tree and f i is the ith function signature from the set of function signatures F.

N ) − k Θ2 2ν (6) where the superscript j denotes the training data index and ν denotes a penalty factor. At the optimum parameter value, the derivate of the objective function is equal to zero. The solution of the system of equations j j i j j f k (ti , ti−1 , wi ) − j j i t,t j f k (t, t , wi ) p(t, t , wi ) − Θ ν (7) yields the optimum parameter vector. The main shortcoming of this model is that it considers a sentence as a linear chain. Classic grammar models like TAG (tree adjoining grammar) are based on this approach.

1 Introduction Communication with most computer systems happens via user-friendly but not natural ways. People need to fill in forms, click buttons, or type instructions through a keyboard instead of giving commands in a natural language to the system. Natural language processing is an increasingly popular area of artificial intelligence for applications such as controlling robots, automotive systems, navigation systems, etc. The main interaction form between human and computer is speech in spoken dialog systems (SDS).

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