Abstract

Abstract: Melanocytic tumors as Benign or Malignant can be diagnosed using different methods. One such method is a Digital Dermoscopic Image. Many conventional methods employ Support Vector Machines (SVMs), K- Nearest Neighbor (KNN), Adaboost, etc have been widely used for lesion classification. An Artificial Neural Network (ANN) is a computational model based on the structure and functions of biological neural networks. ANN can be used widely for medical diagnosis and tumor detection. There are various ANN that can be employed for this purpose. Our proposed method employs BPNN for melanoma classification on Dermoscopy images. We develop a novel method for classifying melanocytic tumors as Benign or Malignant by the analysis of digital dermoscopic images.

Keywords: Dermoscopy image, Benign, Malignant, BPNN (Back Propagation Neural Network)

Abstract: When more than one source is available for a given load, the sources may be utilized in a better manner to supply power efficiently to the load.  In this project we consider two sources such as solar panel and wind energy. Both these are renewable energy sources and the production capacity of these depends upon a large number of external features. The project houses a DC bus in which both the powers generated by wind and solar are given to the load. Depending upon the load requirement only solar or the wind can be made to supply power. Using low voltage DC for the nano grid provides various advantages such as easier integration with renewable sources and battery banks, increased savings, etc.Future systems would use renewable sources and storage devices to become self-sufficient in generation with bare minimum   consumption from the grid. The project houses current and voltage sensors for measuring the power output of the solar panel and the wind energy. As the whole process takes place automatically there is a very lesser need for human interference and the electricity losses during the distribution can be saved on a huge scale.

Keywords: Power supply, Nano grid, Solar panel, Battery

Abstract: In this paper, we introduce taxonomy for classification of faults such as under voltage, overvoltage, over current and frequency variations and isolate the faulty zone at distribution side in a power system. The power demand is increasing and also the management of electric power distribution system is becoming more complex. The effective detection and correction of the faults in distribution side still remains an enigma to the power company. Such situations will lead to power disruption of a wide area. The existing system offers unlimited access to the usage of energy which in turn leads to massive power wastage. The proposed system is useful for facilitating alternative supply to an emergency load from nearby healthy zone. The proposed system also controls demand by shedding loads whenever the load exceeds the peak limit and is also provided with an innovative scheme for theft detection and monitoring of electrical power theft in the electrical distribution system.

Keywords: CT-Current Transformer; PT-Potential Transformer; ZCD- Zero crossing detector

Abstract: Melanocytic tumors as Benign or Malignant can be diagnosed using different methods. One such method is a Digital Dermoscopic Image. Many conventional methods employ Support Vector Machines (SVMs), K- Nearest Neighbor (KNN), Adaboost, etc have been widely used for lesion classification. An Artificial Neural Network (ANN) is a computational model based on the structure and functions of biological neural networks. ANN can be used widely for medical diagnosis and tumor detection. There are various ANN that can be employed for this purpose. Our proposed method employs BPNN for melanoma classification on Dermoscopy images. We develop a novel method for classifying melanocytic tumors as Benign or Malignant by the analysis of digital dermoscopic images.

Keywords: Dermoscopy image, Benign, Malignant, BPNN (Back Propagation Neural Network)

Abstract: When more than one source is available for a given load, the sources may be utilized in a better manner to supply power efficiently to the load.  In this project we consider two sources such as solar panel and wind energy. Both these are renewable energy sources and the production capacity of these depends upon a large number of external features. The project houses a DC bus in which both the powers generated by wind and solar are given to the load. Depending upon the load requirement only solar or the wind can be made to supply power. Using low voltage DC for the nano grid provides various advantages such as easier integration with renewable sources and battery banks, increased savings, etc.Future systems would use renewable sources and storage devices to become self-sufficient in generation with bare minimum   consumption from the grid. The project houses current and voltage sensors for measuring the power output of the solar panel and the wind energy. As the whole process takes place automatically there is a very lesser need for human interference and the electricity losses during the distribution can be saved on a huge scale.

Keywords: Power supply, Nano grid, Solar panel, Battery

Abstract: Farmers today spend a lot of money on machines that help to decrease labour and to increase the yield of crops but profit and efficiency are less. Agricultural automation is the only method to overcome this problem. The robot proposed here is capable of performing operations like automated ploughing, fruit picking and pesticide spraying. The controlling technology is Raspberry Pi which is the brain of the system that supervise the entire operation. Manual control can also be provided with the help of GSM. The main aim is to increase the crop production with increased efficiency.

Keywords: GSM, Raspberry Pi