Manuscripts

Recent Papers

Research Paper

Software Defect Prediction using Ensemble Learning Survey

Machine learning is a science that explores the building and study of algorithms that can learn from the data. Machine learning process is the union of statistics and artificial intelligence and is closely related to computational statistics. Machine learning takes decisions based on the qualities of the studied data using statistics and adding more advanced artificial intelligence heuristics and algorithms.

Published by: Ramandeep Kaur, Er. Harpreet Kaur, Er. Jaspreet Kaur,

Author: Ramandeep Kaur

Paper ID: V2I3-1177

Paper Status: published

Published: June 15, 2016

Full Details
Review Paper

Review of Diabetes Detection by Machine Learning and Data Mining

The most common action in data mining is classification. It recognizes patterns that describe the group to which an item belongs. It does this by examining existing items that already have been classified and inferring a set of rules. Similar to classification is clustering. The major difference being that no groups have been predefined. Prediction is the construction and use of a model to assess the class of an unlabeled object or to assess the value or value ranges of a given object is likely to have. The next application is forecasting.

Published by: Preeti Verma, Inderpreet Kaur, Jaspreet Kaur, ,

Author: Preeti Verma

Paper ID: V2I3-1176

Paper Status: published

Published: June 15, 2016

Full Details

Study Of Various Vehicle Detection Techniques –A Review

ABSTRACT- The Vehicle detection is method to detect the vehicles in the image or video data. The vehicle detection is the branch of the object detection, where the vehicle is the primary object. The vehicle detection can be performed on various kinds of the vehicle data obtained from the horizontal, aerial, parking or road surveillance cameras. In this paper, the vehicle detection and classification method has been proposed by using the hybrid deep neural network over the image data and video obtained from the aerial and satellite images to determine the vehicle density. The non-negative matrix factorization (NMF) will be utilized for the feature extraction and compression for the purpose of vehicle detection and classification. The 2nd level feature compression will be performed to create the quick response vehicle detection and classification system. The model will be programmed to detect the maximum vehicles visible as full or partial object in the image. The vehicle density reporting, vehicle movement reporting and upside & downside reporting for highways will be performed to achieve the goal of the vehicle detection and classification. The aim of this review is to produce the robust algorithm to detect and analyze the vehicle features like whether the vehicle is heavy or light in the images and videos with higher accuracy and precision.

Published by: Geetika Garg, Amardeep Kaur

Author: Geetika Garg

Paper ID: V2I3-1174

Paper Status: published

Published: June 15, 2016

Full Details

A Novel Hybrid Classification Technique for Blur Detection

Image, audio and video are the popular entertainment and communication services of internet. Sometime they suffer from many problems, Blur is one of them. Blur is a factor that breakdown the status of image. In this paper, we are going to perform comparison of four different Blur Detection classifiers. This paper introduces our proposed technique (Hybrid Classifier). To verify the accuracy of hybrid Classifier we collect 1000 images from internet and hence results are predicted. From result and discussion, it is clear that Proposed Classifier give 96% accuracy which is 10% more than existing Classifier (SVM).

Published by: Indu Kharb, Abhishek Sharma

Author: Indu Kharb

Paper ID: V2I3-1173

Paper Status: published

Published: June 14, 2016

Full Details

Document Image Binarization Technique for Degraded Document Images by using Morphological Operators

Segmentation of badly degraded document images is done for discriminating a text from background images but it is a very challenging task. So, to make a robust document images, till now many binarization techniques are used. But in existing binarization techniques thresholding and filtering is an unsolved problem. In the existing method, edge based segmentation can be done and Canny edge detector used. In our proposed technique, Image Binarzation for degraded document images has being use Region based segmentation. Firstly, an RGB image covert into gray image then image filtering can be done on the basis of Wiener Filtering and Gaussian filter. Secondly, morphological operators use to discriminate foreground from background. Then Otsu and Sauvola’s thresholding did for better results. Finally, proposed method results compare with the method used in DIBCO 2011 dataset. The evaluation based on few parameters like F-measure, PSNR, DRD and MPM. Keywords: Filtering, Morphological operators, and thresholding.

Published by: Divya Jyoti, Bodh Raj, Kapil Kapoor, Arun Sharma

Author: Divya Jyoti

Paper ID: V2I3-1172

Paper Status: published

Published: June 14, 2016

Full Details

Implementation of Value Stream Mapping Methodology in Bearing Industry

Lean manufacturing is best way for the reduction of non value added cost, lean word defined by Crafcik in the book of “the machine change the world” in 1988. Lean means thinner and thinner as well as possible to reduce the cost. Lean manufacturing gives the benefit without investment with some modification. In this paper study of the bearing industry at Ahmadabad, Gujarat, for reduction of product lead- time and fulfill the customer demand. This industry is not fulfilling the customer demand and that cause increase the production lead time. In this study to selecting the medium size spherical roller bearing and apply the value stream mapping techniques for detecting the flow of non value added cost with the help of current state map and after analyze it and then prepare a future state map for the proposed implementation. And after apply the entire proposed lean tool and derive the benefits and fulfill the customer demand with reducing lead time.

Published by: Mehul Mayatra, Mr. N.D. Chauhan, Mr. Parthiv Trivedi, Mr. M.N. Qureshi

Author: Mehul Mayatra

Paper ID: V2I3-1171

Paper Status: published

Published: June 13, 2016

Full Details
Request a Call
If someone in your research area is available then we will connect you both or our counsellor will get in touch with you.

    [honeypot honeypot-378]

    X
    Journal's Support Form
    For any query, please fill up the short form below. Try to explain your query in detail so that our counsellor can guide you. All fields are mandatory.

      X
       Enquiry Form
      Contact Board Member

        Member Name

        [honeypot honeypot-527]

        X
        Contact Editorial Board

          X

            [honeypot honeypot-310]

            X