No abstract

The fractal image compression technique has an unique feature due to which physical position of blockslregions in the input image can be extracted directly from the compressed data. Applying this technique, +-q-n partial discharge (PD) patterns (treated as an image) are compressed and stored as affine transformations. These transfornations then are used directly to extract the embedded pattern features, which are classified by a neural network. The novel route to PD pattern classification described in this paper thus addresses both the tasks of compression and feature extraction in a single step. The task of compression is essential to store and handle large quantities of pattern data acquired, especially during on-line monitoring of PD in power apparatus. Results presented illustrate that this approach can address satisfactorily the tasks of compression and classification of PD patterns.

In this paper, we describe about the wireless sensor networks (WSN) in which are used to monitor the physical conditions and co-operatively send the messages of the sensor to the main location. The existing system has been focused on detecting abnormal heart rate by placing the sensor on the pacemaker during bypass surgery. If any abnormalities found, then the warning message has been sent to the patient's relatives. But the issues in the system are, they cannot discuss about the network [41] lifetime and tracking of the patient's location. Our system helps in finding the abnormalities of heart beat rate and also medicine intake by the patient using Bayesian algorithm. The paper highlights the need of personal caring of the patient by the hospital that will reduce unnecessary delay in providing treatment to a patient. It also concentrates on the network lifetime maximization and distance metrics while moving from one network to another network.

Wireless reprogramming during a wireless detector network (WSN) is that the method of propagating a replacement code image or relevant commands to detector nodes. As a WSN is sometimes deployed in hostile environments, secure reprogramming is and can continue to be a significant concern. Whereas all existing insecure/secure reprogramming protocols square measure supported the centralized approach, it\'s necessary to support distributed reprogramming during which multiple licensed network users will at the same time and directly reprogram detector nodes while not involving the bottom station. Terribly recently, a novel secure rationalize and distributed reprogramming protocol named SRDRP has been planned, that is that the initial work of its kind. However, during this paper, we have a tendency to establish associate inherent style weakness within the increased signature verification of SRDRP associated demonstrate that it\'s at risk of associate impersonation attack by that an resister will simply impersonate any licensed user to hold out reprogramming. Later on, we have a tendency to propose a straightforward modification to mend the known security drawback while not losing any options of SRDRP. Our experimental results demonstrate that it\'s able to eliminate the planning weakness by adding one-B redundant information which the execution time of the prompt answer during a 1.6-GHz laptop personal computer is not any quite one ms. Therefore, our answer is possible and secure for real-world applications. Moreover, we have a tendency to show that, so as to additional improve the safety and potency of SRDRP; any higher established identity-based position formula will be directly utilized in SRDRP. Supported implementation results, we have a tendency to demonstrate potency improvement over the initial SRDRP.