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This paper presents a new algorithm for nighttime contrast enhancement. The proposed algorithm modifies the traditional histogram equalization algorithm to maintain the color information of the original nighttime images. The algorithm has a low computational cost that makes it suitable for real-time hardware implementation. In addition, its efficient hardware implementation is detailed on a Xilinx...
The Multi-agents computing paradigm offers support for large scale, widely distributed, high-performance computational systems. Several of such architectures and frameworks have been developed aimed at primarily computations in support of scientific, engineering calculations and managements. On the other hand agent software provides a number of issues including; autonomous, integrity, flexibility,...
Security problems arise in software systems are very challenging. Using program analysis techniques and some language based security rules can help in enforcing application-level security through control access to program resources and verification of control flow of the information inside the program based on some security properties. This paper presents a new job analyzer component for an intrusion...
In group decision making problems is common the necessity of achieving a consensus before making a decision. Many consensus reaching processes have been introduced in the literature but not many intelligent systems have finally been implemented to deal with such processes. In this contribution an initial prototype of a consensus support system supported on a multi-agent paradigm is presented, showing...
Techniques exist to synthesize software architecture using genetic algorithms that employ transformations based on mutations and crossover. In this paper, we demonstrate that complementary crossover can significantly improve this technique. We study two versions of complementary crossover, one in which parents are selected so that they complement each other but the genes are inherited randomly from...
A new time series prediction architecture is introduced using a fuzzy inference system (FIS) and a new framework for fuzzy relational clustering of time series. The FIS is used to predict future samples in a time series where recurrent neural networks comprise the consequents of the rules. The antecedents come in the form of fuzzy relations; however, previous approaches such as FCM build these antecedents...
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