To study the correlation between perinatal outcome & histopathological changes of placenta in cases of oligohydramnios. MATERIALS AND METHODS: The Study was carried out on I 100 antenatal women with oligohydramnios who attended Government Victoria hospital, Visakhapatnam from January 2009 to June 2010. This was a hospital based cross sectional study and objective of the study is to evaluate Oligohydramnios at various gestational ages, associated maternal & fetal risk factors and there outcome will be assessed by mode of delivery and prenatal outcome with histopathological changes of placenta. RESULTS: The caesarean section rate for fetal distress and low birth weight babies <2.5 KG was higher in patients with oligohydramnios, the severity of pathological changes also correlated well with poor perinatal outcome. CONCLUSION: Oligohydramnios has a significant correlation with caesarean section for fetal distress and low birth weight babies along with abnormal histopathological changes in placenta.
Now a days, web content over the World Wide Web is growing fast, it has become tougher to satisfy the necessities of the client’s queries results. This paper provides a technique for advising a sequence of queries that are similar with the client’s input search. The related searches are based on past given searches by the clients itself. This method tells about the clustering process where syntactical or semantically similar searches in groups are found. This also proposes some queries which are similar or related to the queries submitted by the client to get the required information which is relevant and efficient. This method does not only detect the similar and related searches and queries but can also rank them considering the similarity measure. And this technique is executed using real data sets from search engine query log. It gives queries in websites like Google, yahoo, Bing etc.
Data science is a very visual field of computer science where everything needs to be depicted graphically in order to derive new forms of data and conclusions from it. This paper introduces visualization techniques where graphs can be better rendered using advance techniques such as vertex and edge clipping against the view port, rendering a large drawing area by panning the view port to focus on a specific region, labelling vertex data with numeric , text and images and advanced analytic algorithms such as analyzing and finding the shortest path between two vertices using Dijkstra’s, Floyd, finding the minimum spanning tree using Prims and Kruskal’s and traversing all vertices in a graph using Breadth first search and Depth first search. Practically any issue if it can be condensed into a graph data structure format can be sent to this program and are graphically evaluated to discover new information. This paper explains the above-mentioned techniques in detail and how they can work together to create an advanced visualization tool for data scientists working with bidirectional weighted relational data that is graphs.
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