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Research Paper

3-DPGR (3-level Daubechies wavelet, PCA, GLCM and RBF Kernal) method used for brain MRI categorization

Abnormal growth of cells in the brain is called a brain tumor. A brain tumor consists of a collection of abnormally functioning brain cells that have begun to grow and reproduce inappropriately. The uncontrolled growth of a group of cells compresses and damages normal brain structures, which causes a variety of neurological symptoms. According to the reports of National Cancer Institute, Primary brain tumors are the leading cause of tumor cancer deaths in children, now surpassing acute lymphoblast leukemia and are the third leading cause of cancer death in young adults ages 20 to 39. There are more than 120 different types of brain tumors, making effective treatment very complicated. As per classification system defined by the World Health Organization (WHO), a brain tumor is named for the cell type of origin. Brain tumors can either originate from within the brain or from cancer cells that have metastasized from other organs or tissues. Various techniques are developed in the past to detect brain tumor. This research work proposed a Modified Technique for Brain MRI Categorization using 3-DPGR (3-level Daubechies wavelet, PCA, GLCM and RBF Kernal) Method.

Published by: Bharti, Bharti, Manit Kapoor, Dr. Naveen Dhillon

Author: Bharti

Paper ID: V5I4-1163

Paper Status: published

Published: July 19, 2019

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Research Paper

Determinants of customer satisfaction of E-shopping: A study on special reference to Idukki District

Online shopping is the process whereby consumers directly buy goods, services etc. from a seller interactively in real-time without an intermediary service over the internet. Online shopping is the process of buying goods and services from merchants who sell on the Internet. Since the emergence of the World Wide Web, merchants have sought to sell their products to people who surf the Internet. Shoppers can visit web stores from the comfort of their homes and shop as they sit in front of the computer. Consumers buy a variety of items from online stores. As far as e-Commerce business is concerned, ensuring a high level of online customer satisfaction remains an integral, eternal element in achieving and maintaining long-term business success. This study is intended to study customer satisfaction using E-commerce based on a sample from Idukki district. And also analyze and summaries the specific elements of E-commerce customer satisfaction and the various elements of customers expectations and perceptions

Published by: Jinu Joy

Author: Jinu Joy

Paper ID: V5I4-1215

Paper Status: published

Published: July 19, 2019

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Review Paper

A review paper on: Heart disease data set analysis using data mining classification techniques

Health care industry is one of the fastest growing industries in 21st century. This is the era of increasing health problems and chronic diseases. The major chronic diseases faced world over are cardio vascular diseases such as stroke and heart attacks. Heart disease is one of the common causes of death worldwide. According to WHO as many as, 17.9 Million people die of Cardio Vascular Diseases each year, 31% of all the deaths worldwide. Diagnosis of the disease is one of the most important task of medical science. Medical professionals need a decision support system for early prediction of heart diseases with good accuracy rate which can be achieved with the help of data mining techniques. The healthcare industry produces large amount of data each day. Data mining helps in extracting hidden information and patterns from a large and complex database which is helpful in making decisions. The main objective of this research is to develop a heart disease prediction system by using data mining techniques with a good accuracy rate. Here we have a pre processed data set consisting of 303 records and 14 predictors such as Gender, blood pressure, chest pain type etc. as input for BPN and Decision Tree. In this research we will compare two data mining algorithms: Decision tree and Back propagation network Algorithm and predict the presence or absence of heart disease in a patient. The algorithm with highest accuracy rate will be considered good for heart disease prediction in hospitals.

Published by: Shreya Kalta, Keshav Kishore, Aman Kumar

Author: Shreya Kalta

Paper ID: V5I4-1195

Paper Status: published

Published: July 19, 2019

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Review Paper

Scheduling of task in cloud using a different algorithm and its comparison

Distributed computing is viewed as a trendy expression in the present IT industry with the assistance of which clients can gain admittance to programming, equipment, applications, stage by the methods for only a web association. It depends on the idea of utility registering wherein the client needs to pay according to the utilization. The important necessity in the realm of distributed computing is the planning of errands under certain confinements. The undertaking planning issue can be viewed as the finding or looking through a perfect mapping/errand of the arrangement of subtasks of various assignments over the available course of action of benefits (processors PC machines) with the objective that we can achieve the ideal objectives for assignments. In this paper we are playing out a near examination of the various calculations for their sensibility, plausibility, adaptability concerning cloud situation, after that we endeavor to propose the hybrid methodology that can be grasped to improve the present stage further. With the objective that it can urge cloud suppliers to give a superior nature of administrations.

Published by: Babita Bhagat, P. Sanyasi Naidu

Author: Babita Bhagat

Paper ID: V5I4-1204

Paper Status: published

Published: July 19, 2019

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Research Paper

Peak Signal to Noise Ratio analysis in single image restoration technique

Images have a wide significance these days for detailed observation in different fields like remote sensing, and navigation. When images got captured by the image acquisition equipment, they got affected by environmental effects. These environmental effects are haze, smog, fog which cannot be ignored while acquisition. Such type of effects should be reduced so that images can be accurately observed. These effects can be considered as noise in our work. These effects are difficult to reduce efficiently while acquisition. Therefore, there arises a need for an algorithm to process the noisy image after capturing. In our work, Dark Channel Prior (DCP) technique is used for the de-noising purpose and our focus is on the refining of the estimated transmission map so that a noise-less image can be recovered. The efficient noise reduction is determined by the Peak Signal to Noise Ratio (PSNR) value. PSNR value is the evaluation parameter which is used to determine that the proposed work has improved the performance compared to recently introduced approaches. An analysis of our proposed method and other research work is shown.

Published by: Jyoti Pandey, Dr. Krishna Raj

Author: Jyoti Pandey

Paper ID: V5I4-1226

Paper Status: published

Published: July 19, 2019

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Research Paper

Brain tumor segmentation and classification using neural networks in MRI images

Brain tumor has become a primary hassle among living humans amongst in which gliomas is the maximum common difficulty. So, treatment is done through MRI. Magnetic Resonance Imaging is the most used technique to asses those tumors, wherein MRI restricts manual segmentation in a completely low-priced time, restricting using precise quantitative measurements within the scientific observe. So, a dependable segmentation vicinity unit is required. However, the structural changes amongst mind tumors create segmentation a difficult downside. This paper has a tendency to suggest partner degree automatic segmentation methodology and classification primarily based on Artificial Neural Networks. Using GLCM and shape functions make the proposed paintings extra strong for classification features.

Published by: Vinay Babu

Author: Vinay Babu

Paper ID: V5I4-1219

Paper Status: published

Published: July 18, 2019

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