Cervical cancer is identified as the fourth most recurrent cancer among women across the globe. The cancer is treatable, if identified at the early stage. Pap smear test is the most common and the best tool for initial screening of cancer. Pap smear cell level image analysis is an open issue. The limitation of the analysis is due to the complexity of the cell structure. The smear cell image is composed of cytoplasm and nucleus. The shape and structure of the nucleus determines the cancer prevalence. Segmentation of nucleus is an important step in cancer detection. There are various methods developed for nucleus segmentation. The article proposes multithresholding algorithm to segment cytoplasm and nucleus region from the background. Morphological operations are used for correcting the segmented output. Support vector machine classifier is used for classifying the smear cell as normal or abnormal based on the extracted features of the segmented output. The obtained accuracy of the classifier, sensitivity and specificity for single smear cell are 99.66%, 99.85% and 99.17%.

The electromagnetic spectrum is one of nature’s meagre resources. The requirements of wireless communication cannot be satisfied by the new spectrum allocation plan. A policy of self-driven spectrum allocation results as a result. Cognitive radio (CR) engineering is a brilliant technique to maximise spectrum utilisation in rapidly changing environments by identifying unusable and underutilised bandwidth. One of the information strategies of intellectual radio is range detecting, which uses self-persuaded range allocation techniques to use open range to determine the existence of critical clients in the approved recurrence band. Energy location and cyclostationary highlight recognition are the two main factors that determine range detection. Energy recognition is a key method of range detection, but it becomes discouraging at low signal to noise ratios. With a cost of the highest degree of execution complexity, the critical cyclostationary highlight recognition based on cyclic range assessment may successfully identify weak signs from crucial clients. This project is aimed at implementing a useful range detecting mechanism in a field programmable door show with meticulous precision for CR. The adaptive absolute-self-coherent-restoral algorithm, specifically using the truncation multiplier, is a new spectrum sensing system. The proposed architecture, which makes use of a truncation multiplier, was created using the Xilinx approach. This study suggests an efficient spectrum sensing technique that makes use of the Adaptive Absolute Score (AAS) algorithm and SQRT-based Carry Select Adder (CSLA). The TM-CSLA design includes 228 LUT for the Spartan 6 device, which is fewer than the other architectures.

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