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A Review on the Page Recommendation Model using Machine Learning Approaches

The word “page or product range” means to rank the system to display the results and to provide suggestions to others. In day to day activities we rely on E-commerce ranking system such as the page indexing or product ranking of movies like reviews of movies from newspaper etc These E-commerce ranking basically help us to decide what we should opt for when we have multiple options An E-commerce ranking system (RS) helps people that have not sufficient personal experience or competence to evaluate the, potentially overwhelming, number of alternatives offered by a Web site In their simplest form RSs recommend to their users personalized and ranked lists of items Provide consumers with information to help them decide which items to purchase. In this paper, we have propsoed the improved model for the purpose of product recommendation with the higher accuracy and optimized elapsed time based parameters.

Published by: Ramandeep Sharma, Samarth Kapoor

Author: Ramandeep Sharma

Paper ID: V3I3-1464

Paper Status: published

Published: June 14, 2017

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PSLQ Algorithm: A New Approach In Mathematics Experimental

While extensive usage of high-performance computing has been a staple of other scientific and engineering disciplines for some time, research mathematics is one discipline that has heretofore not yet benefited to the same degree. Now, however, with sophisticated mathematical computing tools and environments widely available on desktop computers, a growing number of remarkable new mathematical results are being discovered partly or entirely with the aid of these tools. For many years, researchers have dreamed of a facility that permits one to recognize a numeric constant in terms of the mathematical formula that it satisfies. With the advent of efficient integer relation detection algorithms, that time has arrived. This article briefly discusses the nature of mathematical experiment. It then presents a few instances primarily of our own recent computer aided mathematical discoveries, and sketches the outlook for the future.

Published by: Manju Devi

Author: Manju Devi

Paper ID: V3I3-1531

Paper Status: published

Published: June 13, 2017

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Laplace Transforms and Its Applications

Laplace transform is a very powerful mathematical tool applied in various areas of engineering and science. With the increasing complexity of engineering problems, Laplace transforms help in solving complex problems with a very simple approach just like the applications of transfer functions to solve ordinary differential equations. This paper will discuss the applications of Laplace transforms in the area of physics followed by the application to electric circuit analysis. A more complex application on Load frequency control in the area of power systems engineering is also discussed.

Published by: Manju Devi

Author: Manju Devi

Paper ID: V3I3-1530

Paper Status: published

Published: June 13, 2017

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Enhance Energy Efficient Low Cost WSN System for Precision in Agriculture Zone

Big amount of data is collected by the sensors from the end Subsequently, this considerably big amount of data must be processed, analyzed and stored in a effective ways. In this manner, an of computing resources and storage be provided to compute this large amount of data. To focused on introducing the latest technologies like as sensors, WSN to revise approaches to agriculture by collecting the data about the various parameters of soil, analyzes the data and performed the computations, giving the best optimal solutions for the farming. The application of computing in agricultural economy will open up a vast range of prospects, such as the vast storage of agriculture information, the cloud management of agricultural production process, the storage of agricultural economy information, early-warning and policy-making based on the agricultural products market, the tracing management of agricultural products quality

Published by: Prashant Suresh Mahure, Amit Fulsunge, Kartik Ingole

Author: Prashant Suresh Mahure

Paper ID: V3I3-1511

Paper Status: published

Published: June 13, 2017

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Digital Money Monitoring

Il an system is to generally audit or maintain the transaction of each and every amount of a individual (i.e) tracking by this way will avoid the black money. If this system is implemented throughout the country then there will be no words will be hearing like black money. the bit coin means that for each and every currency in our application surrendered by the user will be generating the unique id for every currency, when the amount is transferred from source to destination not only the amount and count of the currency will be taken in addition to that unique id will also be transferred so that can track the path of the currency travelling around .If the unique id is not in a rotation then can analyze which is the last account it has entered and from that account it is unseen in this way maintain the auditing.

Published by: S. Divya Bharathi, D. Divya, S. Barath, K. Sakthipriya, S. Vijayalakshmi

Author: S. Divya Bharathi

Paper ID: V3I3-1481

Paper Status: published

Published: June 13, 2017

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Segmentation of Brain MRI Using Multilevel Iterative Discrete PSO Based SVM

Image Segmentation is an important part of image processing which can be used to separate objects in images, ignoring the effects of lights and textures. The higher resolution and better spatial discrimination of soft tissues make MRI an effective method among other medical diagnostic modalities. The existing Particle Swarm Optimization (PSO) technique is not much effective approach since the space for feasible solutions of min – cut partitioning problem is excessively large, particularly when the number of vertices is in the thousands. In this paper, multilevel segregating method is combined with discrete PSO and developed Multilevel Iterative Discrete Particle Swarm Optimization algorithm (MIDPSO) for min – cut partitioning. MIDPSO works in three steps- partitioning phase, refinement phase, and recursive partition. The classifier Support Vector Machine (SVM), based on structured risk minimization is used here. By selecting the best features in the dataset; SVM increases the performance as well as reduces the computational time complexity. The proposed technique considers local as well as global to meet the requirement of precise segmentation. The proposed method aims in classifying the healthy and pathological tissues in the MRI images with high sensitivity, specificity and accuracy in least time.

Published by: Dhanya G. S, Dr. R. Joshua Samuel Raj, Sam Silva A

Author: Dhanya G. S

Paper ID: V3I3-1527

Paper Status: published

Published: June 12, 2017

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