Information Technology

Mobile Ad-hoc Networks (MANET) is the self organizing collection of mobile nodes. The Optimized Link State Routing (OLSR) protocol was designed to improve scalability of Mobile Ad-Hoc Networks (MANETs). OLSR protocol implements Multipoint Relay (MPR) nodes as a flooding mechanism for distributing control information. Nevertheless, OLSR was designed without security measures. There-fore, a misbehaving node can affect the topology map acquisition process by interrupting the flooding of control information or disturbing the MPR selection process.

The object-oriented data model is predicted to be the heart of the next generation of database systems. Users want to move from old legacy databases into applying this new technology that provides extensibility and exhibility in maintenance. However, a major limitation on the wide acceptance of object-oriented databases is the amount of time and money invested on existing database applications, which are based on conventional legacy systems. Users do not want to lose the huge amounts of data present in conventional databases. This paper presents a novel approach to transform a given conventional database into an object-oriented database. It is assumed that the necessary characteristics of the conventional database to be re-engineered are known and available. The source of these characteristics might be the data dictionary and/or an expert in the given conventional database. We implemented a system that builds an understanding of a given conventional database by taking these characteristics as input and produces the corresponding object-oriented database as output. Finally, we handle the migration of data from the conventional database to the constructed object-oriented database.

This paper attempts to signify the importance of newest variation of data mining in form of web mining. The paper also discusses about some of the existing web log analysis algorithms. With the rapidly growing use of www in business sectors involving e-Business, e-CRM, Digital Libraries and so on, there arises a strong need for performing web log analysis to ensure the security of organization and also to drive the growth of any organization. However there exist many systems for performing the web log analysis, the results they generate are far from the expectations. The major challenges for designers of such systems is to develop an efficient analysis algorithm that generate the precise outcome to identify the exact usage pattern of different web users and at the same time find the most common usage pattern.

Ontologies have become the best modeling tool, in many applications majorly semantic web. Creation of ontology remains as a difficult task. Ontology bootstrapping is one of the technique, depends on a set of pre-defined textual sources like web services. The advantage of web services usually consists of both WSDL and free text descriptors. And these are evaluated by three methods namely TF/IDF, web context generation and the bootstrapping technique. The bootstrapping method using large repository of real-world web services has a drawback of revisiting of the concepts again and again. Our proposed method for ontology creation with an revisiting avoidance algorithm, this algorithm helps us to overcome from revisiting strategies in the bootstrapping ontologies. The introduced algorithm will produce the efficient result as described this is paper.

Navigation systems are gaining interest in research and industrial topic due to their wide usage. The method of updating the map database with previously unknown map information has become an important factor in navigation system design. Today, many map DB providers maintain their own datasets and work to reduce unknown map information in only their proprietary maps. Map updating systems is generally based on network and cloud based map generation and updating. This paper introduces the main difficulties associated with determining and updating unknown map information and briefly surveys the state-of-the-art technologies in this field. Further discussion of the cloud oriented DB updating of unknown map information is also provided and its advantages.

In this paper, we review some pattern recognition learning methods and the models published in recent years. After giving the general description of pattern recognition, we discuss the Multi Layer Perceptron algorithm for classification in pattern recognition. Lastly, the example describing the implementation of MLP .The objective of this paper is to summarize and compare some of the methods for pattern recognition, and future research issues which need to be resolved and investigated further are given along with the new trends and ideas

Number of smartphones users is rapidly increasing. With this smartphones usage mobile malware attacks are also growing. Any malicious code or program used to access the information, gain the access or disrupt is known as malware. The developers of the malwares use the third party apps in order to inject the malicious contents into the phones and destroy the security. Various malware detecting tools are used to fight against these malwares. Malware detectors use various techniques for the detection of malwares. The main aim of this paper is to put light on the various malwares, malware detection, limitations and the various features involved.

Frequent pattern mining is a process of mining data as a set of itemsets or patterns from a transactional database which support the minimum support threshold. A frequent pattern is a pattern (ie. a set of items, substructures, subsequences etc.) that occurs frequently in a dataset. Association rule mining is a process of mining data as a set of rules from a transactional database which support the minimum support and confidence. The implementation methods uses special data structures to solve the problem of FPM and ARM. This paper presents some of the data structures for FPM with their advantages and disadvantages.

Mobile computing is an innovative technology, Born as a result of remarkable advances in computer hardware and wireless communication have made mobile computing possible that tens millions of users uses a portable computer device with wireless connection. This technology introduces a term called as mobile database which increasingly uses day by day. Using mobile database technology, mobile user can read and update the database while they are disconnected from the network. In this technology, data is being moved closer to the applications in order to improve the performance and autonomy. But it is having some problems which we will discuss here. As a solution we proposed a module to handle co-ordination between Mobile Host and Server.

This paper presents a deep study on the application of Data mining Techniques in the field of Agriculture. Data mining software applications using various methodologies have been developed by both commercial and research centers. Using this software applications Agricultural eco system is also managed. Eco system management includes soil management. Recent technologies are nowadays able to provide a lot of information on agricultural-related activities, which can then be analyzed in order to find important information .Efficient techniques can be developed and tailored for solving complex soil datasets using data mining.