Bayesian Network and Network Pruning Strategy for XML Duplicate Detection

Data Duplication causes excess use of redundant storage, excess time and inconsistency. Duplicate detection will help to ensure accurate data by identifying and preventing identical or similar records. There is a long work on identifying duplicates in relational data, but only a slight solution focused on duplicate detection in more complex hierarchical structures, like XML data. Hierarchical data are defined as a set of data items that are related to each other by hierarchical relationships such as XML .In the world of XML there are not necessarily uniform and clearly defined structures like tables. Duplicate detection has been studied extensively for relational data. Methods devised for duplicate detection in a single relation do not directly apply to XML data. Therefore there is a need to develop a method to detect duplicate objects in nested XML data. In proposed system duplicates are detected by using duplicate detection algorithm called as XMLDup. Proposed XMLDup method will be using Bayesian network. It determine the probability of two XML elements being duplicates by considering the information within the elements and the structure of information. In order to improve the Bayesian Network evaluation time, pruning strategy is used. Finally work will be analyzed by measuring Precision and Recall value

Identification of Identical Twins using Face Recognition with Results

Face recognition is a process used to identify or verify the person based on digital image from unique face of humans. Face recognition is based on individual and unique person identification. This process fully based on comparing the image with other person image for identification. Face Recognition is typically used in security systems and can be compared with other biometrics such as fingerprint or iris recognition systems. Here, the major problem is to identify twins. To overcome this problem we can use different facial recognition algorithms. The facial recognition algorithms should be able to identify the similar-looking individuals or identical Twins with accurate classification. In the proposed system, image of a person is given as a input then different features of image were extracted by using the Gabor and LBP algorithms. Extracted Features of both the images are compared and then classified using multi-SVM classifier. Based on classification method, the persons were identified to be identical twins or they were identified to be same person or not twins. After Identification, Performance of the process is measured

Face Recognition using SOM Network

This paper presents novel technique for recognizing faces. From the last two decades, face recognition is playing an important and vital role especially in the field of commercial, banking, social and law enforcement area. It is an interesting application of pattern recognition and hence received significant attention. The complete process of face recognition covers in three stages, face detection, feature extraction and recognition. Various techniques are then needed for these three stages. Also these techniques vary from various other surrounding factors such as face orientation, expression, lighting and background. The Self-Organizing Map (SOM) Neural Network has been used for training of database and simulation of FR system. In this paper the feature extraction methods discrete wavelet transform (DWT), discrete cosine transform (DCT) simulated in MATLAB are explained

Implementation of Space-Filling Curves on Spatial Dataset: A Review Paper

Cloud computing is the most recent innovative achievement that everybody ought to know about independent of whether you are a provider or a purchaser of innovative technology. Financial benefits are the essential driver for the Cloud, since it ensures the diminishment of capital utilize and operational utilize. The widespread use of the cloud has lead to the rise of database outsourcing. Privacy and security are the main considerations in the database outsourcing. Most of the conventional approaches provide security to outsourced data either by existing cryptographic techniques or using spatial transformation schemes. Here we propose a system which will implement and compare two space-filling algorithms (Hilbert curve and Gosper curve) on spatial data

Review Paper On: Accident Detection Using VANET

Vehicular ad hoc networks (VANETs) are collecting enlarge recognition from techno based and deployment based sections of industry, due to the various applications and probable immense welfare they offer for future VANET users. Safety information exchange enables life-critical application, such as the alerting functionality during crossing traversing and lane merging, and thus, plays a key role in VANET application. In a VANET, vehicles will depend on the integrity of received data for deciding when to send lerting triggers to drivers. The interaction between car to car, car to roadside unit is done using wireless communication interfaces. That is why sefty is an salient concern area for vehicular grid application. For authentication purpose so many bandwidths is consumed and the production becomes low. In VANET some serious networks attacks such as man in middle attack, impersonation is possible. In this paper we are going to through some light on the previous researches done in this area and will compare the various drawbacks of these researches. After that we are giving different issues on VANET and finally conclude with proposed algorithms. DOI: 10.17762/ijritcc2321-8169.15031

Bibliometric Survey on Effect of Socio-Economic Factors on Spread of Corona virus (COVID-19)

The Novel Coronavirus disease has been rapidly spreading all around the globe, from the time when it was first reported in the Wuhan city of China. The primary focus of this bibliometric survey is to distinguish the documents which have hypothesized and expanded on the effects of various socio-economic factors when it comes to the spread of the Coronavirus. This survey does the evaluation on the 480 documents found. The United Kingdom of the Great Britain and United States have contributed the largest number of publications in this field of research followed closely by India and Italy. The survey includes analysis based on geographical regional, analysis of network, analysis on the basis of type of publication, dialect in which the document is written in. We have also considered the universities, institutes and authors that have contributed in this research area. This bibliometric survey concludes that the highest number publications of “Socio-Economic factors affecting the spread of COVID-19” are from articles, review papers associated with agriculture and biological sciences. The documents that were analyzed are considered from the time period of 2020 to 2021

Keyword Merging Based Multi Document Enhanced Summarization

Automatic text summarization is a wide research area. There are several ways in which one can characterize different approaches to text summarization: extractive and abstractive from single document or multi document. Summary is text that is produced from one or more text. Document summarization is a procedure that building coated version of document that gives respected data to the client, and multi-document summarization is to produce a summary conveying the larger part of data substance from a set of documents about an implicit or explicit primary point.This paper describes a system for the summarization of multiple documents. The system produces multi-document summaries using data merging techniques. For combining multiple document on same thing the system uses Bisecting k-means algorithm which works better than basic K-means algorithm.Our System uses Enhanced Summarization algorithm to summarize multiple document.The Enhanced algorithm is applied separately on each cluster. According to results this system gives better results as compared to NEWSUM algorithm. DOI: 10.17762/ijritcc2321-8169.150711

Implementation of Customized UTP Algorithm for Attack Detection in Multitier Web Applications

Internet services and application have gained lots of importance in our daily life such as banking, travel and social networking. Personal information from any of the remote location can be communicated and managed with the help of Internet. Due to their omnipresent use for daily task, web applications have been target for attack. To deal with increasing demand and data complexity web services and applications have moved to a multitiered design. The idea is to detect attacks in multitier architecture to model the network behavior of user sessions across both the front-end web server and the back-end database. The attacks like SQL injection, cross site scripting attack, privilege escalation attack and direct DB attack can be monitored with both the web and subsequent database requestusing customized UTP algorithm, which an independent system cannot do

A Review on Fake Currency Detection using Image Processing

Paper currency identification is one of the image processing techniques i.e. clothed to recognize currency of different countries. The paper currencies of different countries are collectively rises ever more. However, the main intention of most of the standard currency recognition systems and machines is on recognizing fake currencies. The features are extracted by using image processing toolbox in MATLAB and preprocessed by reducing the data size in captured image. The expose pluck out is discharged by considering HSV (Hue Saturation Value). The chief is neural network classifier and the next step is recognition. MATLAB is used to evolve this program. The new source of paper currency recognition is pattern recognition. But for currency recognition, converter system is an image processing method which is used to identify currency and transfer it into the other currencies as the users need. The need of currency recognition and converters is accurately to recognize the currencies and transfer the currency immediately into the other currency. This application uses the computing energy in differentiation among different kinds of currencies are differentiated with their suitable class using power computing. Fake note at present plays a key topic for the researchers. The recognition system is composed of two parts. First is the captured image and the second is recognition. Forged currencies recognition is the main aim of the standard paper currency identification system. The most mandatory system is currency identification system and it should be very accurate. The performance of different methods are surveyed to refine the exactness of currency recognition system