Our human civilization has encountered many dangerous diseases and death due to lung cancer is increasing worldwide. The finding of lung cancer cells in the earliest stage is the most challenging process in the medical field. To address the issue, digital image processing techniques, along with neuro-fuzzy logic, has experimented in this current study. The system is aimed to help in the initial stage detection of lung nodules by classifying the existence of abnormalities in the computed tomography (CT) scan image. The critical stages involved in the detection process are preprocessing, image enhancement, image segmentation, feature extraction and neuro-fuzzy algorithm. The proposed system is an entirely functional automatic method which completely avoids physical calculation and this designed system produces a better result with a high accuracy rate.
Digital picture watermarking is employed to stay secret the proprietary info as a watermark within a digital image, to spot the possession. This method has relevancy to any or all pictures. Separate trigonometric function transform (DCT) is employed before inserting the watermark within the host image. The host picture is isolated into 8×8 non-covering hinders preceding DCT application, and therefore the watermark bit is inserted by dynamic distinction between DCT coefficients of contiguous squares. Arnold transform is employed even so disorderly encoding to feature 2-fold block safeguard to the watermark. 3 distinctive variations of the planned calculation are tried and stone-broke down. The reenactment results demonstrate that the planned set up is powerful to the overwhelming majority of the image making ready tasks like JPEG pressure, honing, trimming, middle separating, and so on. To approve the proficiency of the planned technique, the recreation results are contrasted and sure condition of-workmanship systems. The examination results represent that the planned set up performs higher as so much as power, security and imperceptivity. Given the advantages of the planned set up, it alright could also be used in applications like e-social insurance and telemedicine to smartly hide out electronic eudemonia records in therapeutic footage.
Now a days Artificial Intelligence is an emerging technology. Neural network concepts used in many applications at present situation. The usage of internet increases day by day as well as the lack of security increases day by day. Mainly phishing scams emerges highly in case of network security. In this paper Neural network concepts, how to train and test the data using Artificial neural network has been discussed which gives an brief idea about usage of Neural net concepts in field of Network security. The properties such as feed forward back propagation network form, gradient descent momentum training purpose, sigmoid transfer function, supervised learning model used to train the model for predicting fraudulent attacks.
Reconfigurable antennas (RA) are capable of dynamically altering their frequency, polarization, and radiation properties in a controlled and reversible manner. They modify their geometry and behaviour to maximize the antenna performance in response to changes in their surrounding conditions. To implement a dynamical response, they employ different mechanisms such as PIN diodes, varactors, radio-frequency microelectromechanical systems (RF-MEMS), FETs, parasitic pixel layers, photoconductive elements, mechanical actuators, metamaterials, ferrites, and liquid crystals. These mechanisms enable intentional distribution of current on the antenna surface producing reversible modification of their properties. This chapter presents the design process and applications of RA. The latest advances on reconfigurable metamaterial engineering, and the current trends and future directions relating to RA are reviewed. Finally, the applications of RA in cognitive radio, multi-input multi-output (MIMO) systems, satellite communications, and biomedical devices are highlighted.
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