Text mining refers to the process of deriving high-quality information from text. Text processing involves in search and replace in electronic format of text. A number of approaches have been developed to represent and classify text documents. Most of the approach tries to attain good classification performance while taking a document only by words. We propose a concept based methodology instead of terms. It represents the meaning of text to reduce the features. Support Vector Machine (SVM) algorithm is applied for document classification. Then the performance measure is compared with document classification using original features and concept based features. This methodology enhances the document classification accuracy.

Web services are utilized to illuminate some particular assignment. When a single web service cannot solve a given task, several web services are composed. Composition can be done either statically at design time or dynamically at runtime. Dynamic composition is more suitable for business applications where in business policies and user requirements frequently changes. Interleaved dynamic composition and execution of services is beneficial for adapting to changing user preferences. One of the main issues in such a scenario is that whether the component services that are composed operate according to the business rules specified. Safety, liveness and deadlock freedom properties of a composition depend on the behavior of individual services. Existing modeling techniques capture these properties and perform model checking only statically. Hence in this work, a two level model verification approach has been proposed to verify the correctness of dynamically composed services.

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BACKGROUND: Small bowel tumours occur rarely with an average annual incidence rate of 9.9 per million people. (1) Jejunum accounts for only 20-30% of all small bowel cancers. Jejunum cancer is rare accounting for only 3% of all gastrointestinal cancers. (1) We report this case of Jejunal adenocarcinoma for the rarity. We discuss the diagnosis and management of this case briefly.

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