The main concern of this paper is to evaluate the web sources, which are to be selected as external data sources for web warehousing. In order to identify the web sources, they are evaluated on the... Show More

The main concern of this paper is to evaluate the web sources, which are to be selected as external data sources for web warehousing. In order to identify the web sources, they are evaluated on the ground of their multiple features. For it, Multi Criteria Decision Making (MCDM) approach has been used. Here, among all the MCDM approach, the focus is on “Technique for Order Preference by Similarity to Ideal Solution” (TOPSIS) approach and proposing an enhancement in this method. The conventional TOPSIS approach uses Euclidean Distance to measure the similarity. Here, Jeffrey Divergence has been proposed to measure the similarity instead of Euclidean Distance which includes all the symmetric distances during computation. The Euclidean Distance only measures unidirectional distance whereas the Jeffrey Divergence includes multidirectional distances. Unidirectional distance includes only distance in one dimension but multidirectional distances includes differences, so more relevant in web sources evaluation. Experimental analysis for both the variations of TOPSIS approach have been conducted and the result shows the enhancement in the selection of web sources.

Signal enhancement is useful in many areas like social, medicine and engineering. It can be utilized in data mining approach for social and security aspects. Signal decomposition method is an... Show More

Signal enhancement is useful in many areas like social, medicine and engineering. It can be utilized in data mining approach for social and security aspects. Signal decomposition method is an alternative choice due to the elimination of noise and signal enhancement. In this paper, two different algorithms such as Empirical Mode Decomposition (EMD) and Variational Mode Decomposition (VMD) are used. The bands are updated concurrently and adaptively in each mode. That performs better than the traditional methods for non-recursive signals. Further it has been investigated that VMD outperforms EMD due to its self-optimization methods as well as adaptively using Wiener filter. It is shown in the result section. Different noise levels as 0dB, 5dB, 10dB and 15dB are considered for input signal.

A considerable amount of time is required to interpret whole news article to get the gist of it. Therefore, in order to reduce the reading and interpretation time, headlines are necessary. The... Show More

A considerable amount of time is required to interpret whole news article to get the gist of it. Therefore, in order to reduce the reading and interpretation time, headlines are necessary. The available techniques for news headline construction mainly includes extractive and abstractive headline generation techniques. In this paper, context based news headline is formed from long news article by using techniques of core Natural Language Processing (NLP) and key terms of news article. Key terms are retrieved from lengthy news article by using various approaches of keyword extraction. The keyphrases are picked out using Keyphrase Extraction Algorithm (KEA) which helps to construct headline syntax along with NLP's parsing technique. Sentence compression algorithm helps to generate compressed sentences from generated parse tree of leading sentences. Headline helps user for reducing cognitive burden of reader by reflecting important contents of news. The objective is to frame headline using key terms for reducing reading time and efforts of reader.

Natural language is the way of communication for normal human beings which includes spoken language, written and body gestures i.e. head gesture, hand gestures, facial expressions and lip motion... Show More

Natural language is the way of communication for normal human beings which includes spoken language, written and body gestures i.e. head gesture, hand gestures, facial expressions and lip motion etc. On the other hand, speech and hearing-impaired people uses sign language for communication which is not understandable for normal people thus they face problems of communication in society. In this problem interpreters are required but the human interpreters are costly and are not an efficient solution. Thus, there is a need of system which will translate the sign language into normal language which will be understandable by normal. The system proposed and explained in the paper is an efficient solution to this problem. In the system, sign recognition is done using CAMSHIFT and P2DHHM algorithm followed by Haar Cascade Classifier. After sign recognition, the language technology techniques of POS tagging and LALR parser are used to convert recognized sign words into English sentence. Till date no any system has worked on sentence framing. Results shows that this system produces 92% of accurate result which will bridge the gap between impaired and Normal people.