Rahul Rishi

Security Aspects in Mobile Ad Hoc Network (MANETs): Technical Review

Mobile Ad hoc networks (MANETs) are a new paradigm of wireless network, offering unrestricted mobility without any underlying infrastructure such as base station or mobile switching centers. Basically ad hoc network is a collection of nodes communicating with each other by forming a multi-hop network. In a mobile ad hoc network, it is much more vulnerable to attacks than a wired network due to its limited physical security, dynamically changing network topology, energy constrained operations and lack of centralized administration. Since all the nodes in the network collaborate to forward the data, the wireless channel is prone to active and passive attacks by malicious nodes, such as Denial of Service (DoS), eavesdropping, spoofing, etc. The intent of this paper is to investigate the security goal, security challenges and different types of active and passive attacks on MANETs.

Efficacy and Tolerability of Prochlorperazine Buccal Tablets in Treatment of Acute Migraine

Objectives.—To study the efficacy and tolerability of prochlorperazine (PCZ) management of acute migraine.

A New Steganography Method for Gray Level Images using Parity Checker

In the present study, we present a new steganography technique for hiding data in images using parity checker. This method uses the concept of odd and even parity for insertion and retrieval of message. This method is an improvement over earlier methods like least significant bit method and 6 th , 7 th bit method [1] for hiding information in images. Our method retains the advantages of above methods but discards the disadvantages of above methods and provides us the optimal results.

Context based Web Indexing for Storage of Relevant Web Pages

A focused crawler downloads web pages that are relevant to a user specified topic. The downloaded documents are indexed with a view to optimize speed and performance in finding relevant documents for a search query at the search engine side. However, the information will be more relevant if the context of the topic is also made available to the retrieval system. This paper proposes a technique for indexing the keyword extracted from the web documents along with their contexts wherein it uses a height balanced binary search (AVL) tree, for indexing purpose to enhance the performance of the retrieval system.

A Domain and Language Construct based Mapping to Convert Natural Language Query to SQL

Database management systems (DBMS) have been widely used for storing and retrieving data. However, databases are often hard to use since their interface is quite rigid in cooperating with users. End user is required to issue SQL query to retrieve information from the database. Thus, a user cannot interact directly because of lack of knowledge about the SQL query form, thus is restricted to available application options. To provide the direct access of user on dataset, some unstructured query processor is required. The present work is an interface that will convert the unstructured text query to structured SQL query. It is an intelligent interface formation between the user and the dataset and defined in three main stages namely Descriptive Database Construction, Unstructured Query Filtration and Mapping Stage. The system provide the robustness in terms to handle the broader range of user queries and is be implemented in java environment on Enterprise Employee Database. General Terms Natural Language Processing, Natural Language Interface to Database.

Extraction of Contextual Relevance of the Web Document using F-P Growth

The crawled web pages should be organized in a fashion where they are more understandable to machine, for producing the results which are meaningful and relevant. The set of web pages can be categorized into different contextual sense if the crawler has the technique to understand their meaning and the domain identification. The contextual relevance of the web documents can be known, if the frequent occurring patterns of the keywords in the web page are identified. This can be achieved through data mining technique for generating frequent patterns, using FPGrowth. It will help in deducing the set of keywords of the documents and this knowledge is added in the knowledge store which will further facilitate in the building the ontology for the crawled web pages and organizing them and thus increasing the rank of the document.

Effect of Annealing Selection Operators in Genetic Algorithms on Benchmark Test Functions

The strategies to find optimal solutions can be broadly categorized into two: exploration and exploitation, but it has been shown in the literature that none can be claimed better than others in all the problems or all stages of the problems. In evolutionary approaches such as genetic algorithm, different operators used are inclined either towards exploration or exploitation but problems demand the operators having the blend of both. In this paper an annealed selection operator has been proposed, the behavior of which is controlled by the current generation i.e. in early cycle of evolution it is more like exploration and gradually it shifts towards exploitation. The experiments have been conducted using five different benchmark functions and implementation is carried out using MATLAB. Results show the improvement over existing selection operators.