Computer Engineering

Web 2.0 has become principle tool for accessing information. With Photo sharing websites like Flickr, Picassa, Zoomr images uploaded by user and their tags are available. But Missing tags and Noise problems among image and tag make it difficult to retrieve relevant image based on user’s preference. This requires tags refinement. We propose a model that utilizes Ranking based multicorrelation tensor factorization model for enriching tags pool. This model does it by constructing ternary relation between User, Image and Tag. RMTF does qualitative analysis on available tag set and find positive example and negative example by finding user, image tag interrelations. Tags are compared based on context relevance and semantic relevance. The proposed model finds better result than previous solutions. Given module is tested for multiple word query and shown attractive results.

The online social media is the great area of research which is explored by the researchers now days. There are number of areas in which overlapping community detection works. In this paper we have done comparison of various algorithms in order to detect the overlapping communities in the Facebook network. The framework for evaluating various algorithms is described which helps in disclosing the person’s membership in multiple clusters. The cluster is a collection of number of distinct users belonging to one or more groups. This paper evaluates the comparison between various algorithms which are used for overlapping community membership detection. Experimental results shows that CPM can give better results in less amount of time.

Rapid growth of technology and prevalent use of computers in the business and other areas, more and more organizations are converting their handwritten paper documents into electronic documents that can be processed by computers. Handwriting recognition has attracted voluminous research in recent times. Optical Character Recognition (OCR) deals with machine recognition of characters present in an input image obtained using scanning operation. It refers to the process by which scanned images are electronically processed and converted to an editable text. Almost all the existing handwritten character recognition techniques use neural network approach, which requires lot of pre-processing and hence accomplishing these problems using neural network is a tedious task. In this paper we propose a novel solution for performing character recognition in TAMIL, the official language of the south Indian province of TamilNadu. Pursued by the pre-processing techniques, Segmentation and Feature Extraction are done for recognizing handwritten Tamil characters, which improves the efficiency. The tolerance of the system is evident as it can overwhelm the complexities arise out of font variations and proves to be flexible and robust. These initial results are promising and warrant further research in this direction.

The goal of this project is to automatically detect and recognize some objects in an image by using a multi-agents architecture. A knowledge database is thus necessary and should contain an invariant description of known objects for the desired application. An agent processes an area of the image, its goal is to detect an object and check if this object belongs to the knowledge database. Point matching is an important aim in the research work. A digital image may undergo any arbitrary translational, rotational changes because of which the object shape may change. In this paper we present a novel approach for shape and feature matching using putative point matching.

Cloud computing is an efficient data sharing technique where users can directly store and access information through internet. Hence the chances of unauthorized access and security of data is an important issue in cloud computing, hence various techniques are implemented for the security of cloud data. Encryption is a technique of providing a secure access of data over internet, but chances of attack is still possible. Hence an efficient technique is implemented using the concept of multi-keyword based data retrieval in cloud computing with encryption [1]. Although the technique is efficient in terms of communication overhead and security from various attacks but further enhancements can be done in the technique to make it for secure and easy, hence a new and efficient technique is implemented in cloud computing using attribute based encryption and verification, the proposed technique implemented provides security from various attacks and provide less storage and communication overhead.

The purpose of this research is review of rules and application area of predictive data mining in medical sciences and presenting a frame work for creating, evaluation and exploitation of data mining models in this. In this paper a new method is presented for the diagnosis of diabetes. In this article we want to use the combination of artificial intelligent techniques such as genetic algorithm for attribute reduction from 8 to 4, the artificial neural decision tree to select the best possible conditions Neural Network, and education to estimate adaptability learn Machine, in order to identify the diagnosis of uses. The present study compared to older methods and meta-heuristic model involving a combination of genetic algorithms and neural networks and decision trees in the diagnosis of diabetes is based on the laws and properties of the compound.

Now a day’s large volume og information is available online. An efficient and effective management of the information on the web is not only valuable to individual users but also to business organizations, especially for decision making purposes. Here challenging task is amongst available information on the web finding business values. The signi?cance of organizations information depends on the applications that deal with it. An organization allows the customer to query online published products information and collects their reviews about the products. XML guarantee about those features of business functions including integration, intelligence and reuse of the content. To complete XML assurance it is very important to maintain XML documents properly. In this paper provides discussion and comparison of various commercial tools and database management systems to create, store, maintain, and query XML documents.

The proposed system applies to all Police stations across the country and specifically looks into the subject of Crime Records Management. It is well understood that Crime Prevention, Detection and Conviction of criminals depend on a highly responsive backbone of Information Management. The efficiency of the police function and the effectiveness with which it tackles crime depend on what quality of information it can derive from its existing records and how fast it can have access to it. It is proposed to centralize Information Management in Crime for the purposes of fast and efficient sharing of critical information across all Police Stations across the territory. Initially, the system will be implemented across Cities and Towns and later on, be interlinked so that a Police detective can access information across all records in the state thus helping speedy and successful completion to cases. The System would also be used to generate information for pro-active and preventive measures for fighting crime. The project has been planned to be having the view of distributed architecture, with centralized storage of the database. The application for the storage of the data has been planned. Using the constructs of SQL server and all the user interfaces have been designed using the DOT Net technologies. The standards of security and data protective mechanism have been given a big choice for proper usage. The application takes care of different modules and their associated reports, which are produced as per the applicable strategies and standards that are put forwarded by the administrative staff.

This paper provides the simulation of 3 state inverter with different materials and compare the Leakage Current. Material which has the less Leakage Current is considered as better material for the designing of inverter. In previous time the mosfet is design by the combination of silicon and silicon oxide now we are using gallium arsenide and silicon dioxide as one combination and gallium arsenide and silicon nitride as another combination.

One of the basic areas of the computer science is Data Structure. Sorting is an important issue in Data Structure which creates the sequence of the list of items. Although numbers of sorting algorithms are available, it is all the more necessary to select the best sorting algorithm. Therefore, sorting problem has attracted a great deal of research as sorting technique is very often used in a large variety of important applications so as to arrange the data in ascending or descending order. This paper presents a Both Ended Sorting Algorithm which is faster or better than the bubble sort& others algorithm. After having studied various sorting algorithms; I came to the conclusion that there is no such sorting algorithm which works on the basis of both end comparison right end as well as left end. The new algorithm so is then analysed, implemented & tested. The test results obtained are then presented and compared with the traditional Sorting Algorithm. Worst case complexity is also improved as a compare to bubble sort.