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Titlebook: Artificial Immune Systems; 11th International C Carlos A. Coello Coello,Julie Greensmith,Mario Pav Conference proceedings 2012 Springer-Ver

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A Negative Selection Approach to Intrusion Detection then presenters engage in a less frustrated dynamics and their abnormal presentation can be detected. The performance of our algorithm is independent of the dimension of the space, i.e., the length of information presented by presenters, and hence does not suffer from the dimensionality curse accompanying current methods.
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A Real Time Anomaly Detection System Based on Probabilistic Artificial Immune Based Algorithm, low false alarm, low computational complexity, and real-time response to the incoming samples. We compare our  proposed method with several  well-known anomaly detection algorithms on various datasets. We demonstrate that the  proposed method performs the best among others in terms of false alarm, detection rate and time response.
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Conference proceedings 2012) is a diverse and maturing area of research that bridges the disciplines of immunology, biology, medical science, computer science, physics, mathematics and engineering. The scope of AIS ranges from modelling and simulation of the immune system through to immune-inspired algorithms and in silico, in vitro and in vivo solutions.
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Herausforderungen experimenteller Forschung,pling between fever and autism is studied using this model. It is shown that fever may shift the level of IL-1, IL-6 cytokines in autistic subjects closer to standard physiological values. This is in accordance with a recent observation that fever improves behavior of autistic children, reported in medical literature.
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Immune-Inspired Self Healing in Wireless Sensor Networks node can detect degradations in network performance, perform diagnostic tests, and provide automated immediate response to recover the network to a stable state. We evaluate and compare the performance of our approach with other routing protocols on a testbed environment using TelosB hardware motes.
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Petri Nets Approach to Modeling of Immune System and Autismpling between fever and autism is studied using this model. It is shown that fever may shift the level of IL-1, IL-6 cytokines in autistic subjects closer to standard physiological values. This is in accordance with a recent observation that fever improves behavior of autistic children, reported in medical literature.
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