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Research Paper

Selective feature processing with k-Nearest Neighbor classification to predict credit card frauds

The predictive analytics are being used in many applications across the globe ranging from financial risk to avalanche studies. In this paper, a new approach is designed to predict the credit card frauds. This approach utilizes the imbalanced feature correction methodology, which eventually reduces the levitation of the features towards one class. The proposed model is designed to filter the credit card data by analyzing the multiple factors to analyze and predict the fraudulent transactions. The proposed model utilizes the maximum-minimum scaling method to scale the quantitative variables on 0-1 scale, after handling the missing values with column mean value. The SVM and KNN based classification method are used to predict the patterns for the credit card frauds. The experimental results have proved the proposed model based on SVM classification as the most efficient algorithm for the purpose of fraudulent pattern prediction. The SVM has been recorded with 99.94% (mean) of accuracy, which is slightly lower than KNN’s 99.95% (mean). Also KNN outperformed SVM on the basis of recall with (approx 91%) and F1 measure (approx 84%) against approx. 84.50% (recall) and approx 82.50% (F1 measure).

Published by: Simranjeet Kaur, Sikander Singh Cheema

Author: Simranjeet Kaur

Paper ID: V4I3-1399

Paper Status: published

Published: May 14, 2018

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Research Paper

Fusing the multimodal Image by simple average, simple minimum, simple maximum, PCA, DWT methods of image fusion – A review

Image fusion is a technique that integrates complimentary details from multiple input images such that the new image gives more information and more suitable for the purpose of human visual perception. This paper presents a review on some of the image fusion techniques (simple average, simple minimum, simple maximum, PCA, DWT). Comparison of all the techniques concludes the better approach for its future research.  

Published by: R. S. Arun Kumar, Dr. K. Suganya Devi

Author: R. S. Arun Kumar

Paper ID: V4I3-1341

Paper Status: published

Published: May 12, 2018

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Case Study

Creating value stream mapping to identify areas of improvements and improve USC mailing process

Undergrad housing of USC receive personal emails, official emails, perishable packages, etc., on a regular basis and it is hence a very important task of the housing department to deliver the mails to the right person without any damage. Mails and packages that are received are numbered and are fed into the system by scanning the tracking number and by assigning the receiver’s name to the tracking number. The process seems to be a fairly simple and effective process that makes sure that no package is lost and no package stays in the mailroom for a long time. But when the process of receiving and sorting is analyzed, we can see that there is a lot of scope for improvement & inventory management. By creating a value stream mapping to identify the areas of improvement, there were many non-value adding steps and a lot of waiting time that lead to an increased cycle time. This paper discusses the improvements that can be implemented in the process steps to make it better and hence increase the efficiency of the service delivered by analyzing the inputs, outputs, inventory and value proposition involved.

Published by: Mahalakshmi Ramasubbu

Author: Mahalakshmi Ramasubbu

Paper ID: V4I3-1375

Paper Status: published

Published: May 12, 2018

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Research Paper

An appraisal of agile DSDM approach

In current generations, software development has been the biggest problem while developing large-scale applications considering the resourced and dynamic changes of client requirement. Scrum software development, when moving forward took the written format as the agile framework was introduced to overcome the problems caused by the conventional software development life cycle (SDLC). Considering the limitations in Business Process (BP) and Xtreme Programming (XP) this paper will focus on Dynamic System Development methodologies (DSDM) which will help to develop the software at a regular pace accepting dynamic changes in client requirements which will help to better planning, optimizing costs, managing, executing and scaling agile process and iterative software development projects.

Published by: Suman Babu Chapram

Author: Suman Babu Chapram

Paper ID: V4I3-1355

Paper Status: published

Published: May 12, 2018

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Research Paper

Estimation of breast tumour size, location and pre-processing algorithm for the breast thermal signatures

Breast cancer is the second most cause of the death among the women in society. Thermography is the non-invasive, non-contact imaging modality that can be used for the early detection of breast cancer. This paper proposes the development of the mathematical model using Penne’s bio-heat transfer equation, and the estimation of the location and the size of the tumour using Metropolis-Hasting (MH) algorithm. This paper also proposes the pre-processing of the thermal images using RGB max filter and Grab-cut algorithm to extract out the region of interest where the probability of the presence of the tumour is more.

Published by: Balwant Singh Rao, Sandesh Shetty, Joshi Manisha Shivaram, V Umadevi, Aradhana Katke

Author: Balwant Singh Rao

Paper ID: V4I3-1380

Paper Status: published

Published: May 12, 2018

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Research Paper

Effect of partial replacement of sand by glass powder and steel powder over the properties of concrete: Implementation

In the present research, a series of experiments had been performed to compare the use of glass powder and steel powder as partial replacement of sand in different proportions. Blended cement prepared by mixing Portland cement with Fly ash in 1:0.5 and 1:1 proportion has been used for this study. Concrete mixes are modified by 10%, 15% and 20% and 25% of glass powder and steel powder in replacement.

Published by: Achal Jain, Nitin Thakur

Author: Achal Jain

Paper ID: V4I3-1356

Paper Status: published

Published: May 12, 2018

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