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Your search keyword '"Elewa M"' showing total 2 results
Start Over Author "Elewa M" Topic artificial intelligence
2 results on '"Elewa M"'

1. Issues on adjointness in multiple-valued logics

Author

Nehad N. Morsi and Elewa M. Roshdy

Subjects
Discrete mathematics, Information Systems and Management, Inference, Computer Science::Artificial Intelligence, Computer Science Applications, Theoretical Computer Science, Conjunction (grammar), Algebra, Artificial Intelligence, Control and Systems Engineering, Close relationship, Rule of inference, Modus ponens, Commutative property, Software, Locard's exchange principle, Associative property, Mathematics
Abstract

We contribute to the theory of implications and conjunctions related by adjointness, in multiple-valued logics. We suggest their use in Zadeh's compositional rule of inference, to interpret generalized modus ponens inference schemata. We provide new complete characterizations of implications that distinguish left arguments, implications that satisfy the exchange principle, divisible conjunctions, commutative conjunctions, associative conjunctions and triangular norms. We also introduce and characterize pseudo-strict and pseudo-continuous implications and conjunctions, and we explore the close relationship between these two notions.

Published
2006
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2. VIRTUAL INSTRUMENTATION BASED SYSTEMS FOR REAL-TIME PATH PLANNING OF MOBILE ROBOTS USING BIO-INSPIRED NEURAL NETWORKS.

Author

HAMMAD, ABDALLAH, YANG, SIMON X., ELEWA, M. TAREK, MANSOUR, HALA, and ALI, SALAH

Subjects
MOBILE robots, ARTIFICIAL neural networks, ARTIFICIAL intelligence, MOBILE communication systems, ROBOTICS
Abstract

In this paper, novel virtual instrumentation based systems for real-time collision-free path planning and tracking control of mobile robots are proposed. The developed virtual instruments are computationally simple and efficient in comparison to other approaches, which act as a new soft-computing platform to implement a biologically-inspired neural network. This neural network is topologically arranged with only local lateral connections among neurons. The dynamics of each neuron is described by a shunting equation with both excitatory and inhibitory connections. The neural network requires no off-line training or on-line learning, which is capable of planning a comfortable trajectory to the target without suffering from neither the too close nor the too far problems. LabVIEW is chosen as the software platform to build the proposed virtual instrumentation systems, as it is one of the most important industrial platforms. We take the initiative to develop the first neuro-dynamic application in LabVIEW. The developed virtual instruments could be easily used as educational and research tools for studying various robot path planning and tracking situations that could be easily understood and analyzed step by step. The effectiveness and efficiency of the developed virtual instruments are demonstrated through simulation and comparison studies. [ABSTRACT FROM AUTHOR]

Published
2011
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