More number of deaths occurring every year due to a common health issue cancer. It is one of the diseases distributed over large area. Among all, lung cancer is most predominant having high death rate. Hence this is most important and a lot of research is going on and to identify lung cancer CT (Computed Tomography) scanned images are used. They provide a picture detailed with growth of tumor and tracks its growth in body so it is better by providing good results compared to other techniques. Therefore in medical fields most of the image processing techniques are used to detect the cancer in its early stages .In this paper we present an approach to detect lung cancer in scanned images. The steps involved in it is proposed using methods of image preprocessing where median filter is used followed by segmentation here mathematical morphological operations are used. Geometrical features like area, perimeter, and eccentricity are calculated to tumor detected part. At last SVM classifier is used to classify whether it is cancerous (Malignant) or normal (Benign).

Automatic speech recognition (ASR) is the process of converting the vocal speech signals into text using transcripts. In the present era of computer revolution, the ASR plays a major role in enhancing the user experience, in a natural way, while communicating with the machines. It rules out the use of traditional devices like keyboard and mouse, and the user can perform an endless array of application s like controlling of devices and interaction with customer care. In this paper, an ASR based Airport enquiry system is presented. The system has been developed natively for telugu language. The database is created based on the most frequently asked questions in an airport en quiry. Because of its high performance, Convolutional Neural Network (CNN) has been used for training and testing of the database. The salient feature of weight connectivity, local connectivity and polling result is a through training of the system, thus resulting in a superior testing performance. Experiments performed on wideband speech signals results in significant improvement in the performance of the system in comparison to the traditional techniques.

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