7th International Conference on Advanced Information Technologies and Applications

July 14~15, 2018, Chennai, India

Accepted Papers

  • Model Transformation Analysis using Reusable Design Patterns: Case Study
    1Indra Gandhi, 2Ave Dasrene,1,2DDepartment of Information Science and Technology, Anna University, Chennai, India

    Model transformation , one of the core component of Model Driven Engineering (MDE) transforms the source model into the target model which intends to meet the stated requirements. However, for these model transformations the required design patterns are not applied effectively. This is due to the lack of well defined structural transformations which may vary across various applications. This paper explores the model transformation required to move towards the target model of the system taken into consideration. Although a noted variation may not be existing in the structural transformation, there exists íní number of variations in the transformation of the system which has been analyzed by performing a model transformation for Unified Payment Interface (UPI), Goods and Services Tax (GST) and MyVisit domain models. The model transformations that has been performed with reference to Entity Relational(ER) Mapping, Entity Merge and Entity Split patterns have been analyzed extensively.

    1Sushmita Tapashetti, 2 Shobha, 1,2Ramaiah Institute of Technology, Bangalore, India

    Agriculture is the broadest economic sector and plays a key role in the overall economic development of nation. There are many issues related to farmers which always hampers the course of our evolution. One of the best solution to tackle these problems is to encourage farmers to use modern techniques as they help in increasing agricultural productivity and cut down the input cost. This paper proposes, solution to measure minerals present in agricultural land such as nitrogen, phosphorous, and potassium as well as humidity, soil moisture and temperature using sensors, LoRa and Cloud technology. The data obtained from the sensors will be collected into the cloud database which will be used to give information to end user. The approach uses the combination of LoRa and cloud computing that promotes the fast development of agricultural modernization and helps to realize smart solution for agriculture and efficiently solve the issues related to farmers from a remote location

    1MEGERSA DESTA JELDU, 2 RUTVIK MEHTA, 1,2Parul University, College of Engg, Vadodara, Gujarat, India

    Developing language application is resource intensive task that requires active participation of stakeholders, from linguistic and computational perspectives. The most explanatory method for presenting what actually happens within Natural Language Processing system is by the levels of language approach. However, if the language has no rule how to write and read, it creates misunderstanding among human beings. Integrating spell checkers in to word processors reduces the amount of time and energy spent to find and correct the misspelled word. Afan Oromo language, Lowland East Cushitic sub-family of the Afro-Asiatic super-phylum language family spoken in Ethiopia has no any spell checking tool yet. Rule Based Afan Oromo Spell Checker is supposed to solve it. In general, the algorithm and techniques used in this study obtains good performance. The result obtain encourages the undertaking of further research in the area, especially with the aim of developing a full-fledged Afan Oromo spell checker.

  • Sentiment Classifier and Analysis for Epidemic Prediction
    Nimai Chand Das Adhikari, Vamshi Kumar Kurva, Suhas S,Jitendra Kumar Kushwaha Ashish Kumar Nayak, Sankalp Kumar Nayak,VaisakhShaj,Analytic Labs Research Group, India

    Intelligent Models for predicting diseases whether building a model to help the doctor or even preventing its spread in an area globally, is increasing day by day. Here we present a noble approach to predict the disease prone area using the power of Text Analysis and Machine Learning. Epidemic Search model using the power of the social network data analysis and then using this data to provide a probability score of the spread and to analyse the areas whether going to suffer from any epidemic spread-out, is the main focus of this work. We have tried to analyse and showcase how the model with different kinds of pre-processing and algorithms predict the output. We have used the combination of words-n grams, word embeddings and TF-IDF with different data mining and deep learning algorithms like SVM, NaÔve Bayes and RNN-LSTM. NaÔve Bayes with TF-IDF performed better in comparison to others.

  • Search Engine Optimization Page Rank Algorithm
    1Ketan sarvakar , 2 Dhruva S. Patel, 1,2U V Patel college of Engineering Kherva, Mehsana, Gujarat, India

    The world of technology and online presence of the giant size corporations have changed the definition of the business as well the marketing of the same. This is supposed to be so mainly because of the availability of the information of every business stack holder on the tips of fingers. However, but the instinct as it remains the same be it a layman or a multi-millionaire, he/she always prefers to buy something that is easily available requiring fewer efforts to search hither and thither. SEO is a technique helping the end-users to find what they want and that too from the choice of their place and brand. This amazing phenomenon takes place due to a well set algorithm that determines the ranking of a particular website for a particular most used keyword on one hand and on the other hand the contents, graphics, website structure and the genuineness of the contents displayed on a web page. This research paper focuses on the core area of SEO- Keywords, Website Contents- On Page Optimization & Off-Page Optimization, and the Algorithm used by search engine to give a rank to a website. As an interesting experiment, I will also use the page rank method on UVPCE website data.