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Ultrasonography is considered to be one of the most powerful techniques for imaging organs for an obstetrician and gynecologist. The first trimester of pregnancy is the most critical period in human existence. This evaluation of the first trimester pregnancy is usually indicated to confirm presence and number of pregnancy, its location and confirm well being of the pregnancy. The first element to be measurable is the gestational sac(gsac) of the early pregnancy. Size of gestational sac gives measure of fetus age in early pregnancy and also from that EDD is predicted. Today, the monitoring of gestational sac is done non-automatic, with human interaction. These methods involve multiple subjective decisions which increase the possibility of interobserver error. Because of the tedious and time-consuming nature of manual measurement, an automated, computer-based method is desirable which gives accurate boundary detection, consequently finding accurate diameter. Ultrasound images are characterized by speckle noise and edge information, which is weak and discontinuous. Therefore, traditional edge detection techniques are susceptible to spurious responses when applied to ultrasound imagery due to speckle noise. Algorithm for finding edges of gsac are as follows. In first step, we are using contrast enhancement, followed by filtering. We are smoothing image using lowpass filter followed by wiener filter. This image is segmented using thresholding. This results in image having large number of gaps due to high intensity around sac. These false regions are minimized by morphological reconstruction. Then boundaries are detected using morphological operations. Knowledge based filtering is used to remove false boundaries. In this prior knowledge of shape of gestational sac is used. First fragmented edges are removed then most circular shape is found as our sac is generally circular. Once sac is located, sac size is measured to predict the gestational age.

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This paper used fuzzy logic theory to study the behavior of a simple pulse width modulated three phase voltage controlled VSI, which feeds a weak ac network with power produced from an offshore wind farm (WF) of induction generators. Its control system, which is based on fuzzy controllers, manages to offer very satisfactory performance. Using Matlab simulation, the study was performed under both steady-state and transient conditions. The results have proven an excellent performance and verified the validity of the proposed system. The studies have also demonstrated the ability of the advanced inverter to assist the system keeping the ac voltage fluctuations in the point of common coupling at an acceptable level.

The effect of noise and occlusion on parametric eigenspace is studied in depth in this paper in order to identify the response of the system for distorted inputs from different sources and environmental factors. The eigenspace method [1] of Murase become very popular due to its ability of automatic visual learning and power to capture the parametric details of the object with low memory. The work done is aimed towards analyzing the different factors that may affect the performance of the system.Paper discusses the effect of number of images used and effect of number of principal components used while training, on recognition system with highly correlated objects with experimental analysis. The work is also carried out for the effect of variation in universal PC for noise and occlusion with correlated and non correlated objects. The work also focuses on memory utilization of system.