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Building an efficient Intrusion Detection System (IDS) is a challenging task in wireless ad hoc networks due to the resource constraints and lack of a centralized control. In this work, we present a decentralized monitor-based IDS for detecting jamming type Denial of Service (DoS) attacks at the lower layers of the protocol stack. The varying channel and network dynamics in ad hoc networks can impair service similar to a jamming scenario, resulting in false positives on intrusion detections. To this end, we incorporate a cross-layer design in our IDS to differentiate the malicious jamming behavior from genuine network failures. We validate our design through simulation, and establish the effectiveness of the model. From the simulation results, we observe a significant improvement in the accuracy of detection and lower false positives.

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Leukemia is a hematologic cancer which develops in blood tissue and triggers rapid production of immature and abnormal shaped white blood cells. Based on statistics it is found that the leukemia is one of the leading causes of death in men and women alike. Microscopic examination of blood sample or bone marrow smear is the most effective technique for diagnosis of leukemia. Pathologists analyze microscopic samples to make diagnostic assessments on the basis of characteristic cell features. Recently, computerized methods for cancer detection have been explored towards minimizing human intervention and providing accurate clinical information. This paper presents an algorithm for automated image based acute leukemia detection systems. The method implemented uses basic enhancement, morphology, filtering and segmenting technique to extract region of interest using k -means clustering algorithm. The proposed algorithm achieved an accuracy of 92.8% and is tested with Nearest Neighbor (kNN) and Naïve Bayes Classifier on the dataset of 60 samples.

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