Semantic processing is an essential task in natural language processing. In semantic processing it has observed that some words have more than one meaning. Multiple meanings of a word create serious problems to linguists which produces ambiguity in sentence. Word Sense Disambiguation is one of the main challenges in natural language processing which is present in almost all the languages. By existing knowledge and experience human can certainly disambiguate the words but for machine it is difficult task. In the proposed work, we are resolving the ambiguity of all open class word in English sentence and translating it to the Hindi sentence. We have used decision tree as a classifier. For improving the speed of translation we have used the concept of translation memory.

 Abstract: A Wireless Sensor Network is a set of sensor nodes that are integrated with a physical environment. This tiny sensor node capable of sensing physical phenomena and it can process the sense data. Sensor nodes radio range is short so they transfer data in a multihop manner to form network which will send network activities to base station. Data transmission consumes much more energy than computation. So to overcome this problem data aggregation technique can be useful. This approach reduces energy consumption by avoiding repeated data. Security in wireless sensor network is also one of the important issues. Some properties of a WSN make it more harmed by certain types of attackers, compared to traditional wired network. Furthermore, constrained devices create their own problems for wireless sensor network. As sensor node is powered by batteries and node required lot of energy to perform some complex computation. So it is important to prevent every node in computation process which will save energy to gain longer network life. The focus of this work is provides confidentiality protecting hierarchical concealed data aggregation for WSN using privacy homomorphism. End to End HomomorphicPaillier cryptoscheme is used to achieve proposed approach.

Abstract: Cache memory management has recently become one of the most crucial research topics in the area of high performance computing. The cache memory has gained popularity due to its capability to offer faster access compared to main memory so processor can access data directly through cache very efficiently. As processor execution speed is faster than accessing memory so the goal is to keep programs rapidly accessible for processing. Cache memory helps not only to access data quickly but also improves the performance of the system. Various cache management policies have been developed to improve the performance of the system. In this paper we focus the issues related with the existing replacement policies and present a new algorithm to overcome these issues. In this paper, we proposed Integrated Cache Scheduling Replacement Algorithm (ICSRA) that will remove the object on the basis of integration of all the parameters like size, frequency and recency if the cache is full. This algorithm consider all size of object to replace with the condition of frequency and timestamp parameter to reduce the cache pollution [1]. Cache pollution means the cache unnecessary waste its space by holding such an object which is no longer be accessed. ICSRA helps to enhance the utilization of cache memory in an efficient manner as well as maximize the cache hit ratio to improve the performance of the system. A detailed classification has also been included based on different parameters which are depending on the analysis of the existing techniques.