A Computational Approach to Predict the Severity of Breast Cancer through Machine Learning Algorithms

Breast cancer is one type of cancer which causes from breast tissue. A lump in the breast, skin dimpling, breast shape changes, fluid from the nipple, or a red scaly patch of skin are some of signs of breast cancer. In the world, cancer is one of the most leading causes of deaths among the women. Among the cancer diseases, breast cancer is especially a concern in women. Mammography is one of the methods for finding tumor in the breast. This method is utilized to detect the cancer which is helpful for the doctor or radiologists. Due to the inexperience�s in the field of cancer detection, the abnormality is missed by doctor or Radiologists. Segmentation is very expensive for doctor and radiologists to examine the data in the mammogram. In mammogram the accuracy rate is based on the image segmentation. The recent clustering techniques are presented in this paper for detection of breast cancer. These Classification algorithms have been mostly studied which is applied in a various application areas. To maximize the efficiency of the searching process various clustering techniques are recommended. In this paper, we have presented a survey of Classification techniques

Sea Breeze Detection with Acoustic Radar

176-181A preliminary study on sea breeze fronts has been made at Visakhapatnam using a monostatic acoustic radar situated in the University campus, very near to the sea shore. During the summer of 1980 sea breeze was almost a daily phenomenon at Visakhapatnam, and was usually seen as a well marked distinct change in the character of the acoustic radar records. The increased thermal turbulence associated with the transfer of heat from the surface into the layer of marine air produced enhanced sound scattering up to the height of 150 m. The sea breeze often created an elevated layer usually in the height range 200-500 m. Acoustic backscatter records obtained in May 1980, when the sea breeze was strongest, are presented and discussed in the light of the prevailing weather conditions and previous experimental studies reported from this station