Article Per Year (5 Year)
p-Index From 2019 - 2024
0.408
P-Index
This Author published in this journals
All Journal IJEE (International Journal of Engineering Education)
Rajakumar B R
Resbee Info technologies Private Limited
Education Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Optimized Active Contor Segmentation Model for Medical Image Compression: Introduction to Improved Marriage in Honey Bees Optimization Shabanam Shabbir Tamboli; Rajasekhar Butta; Rajakumar B R; Binu D; Abhishek Bhatt
International Journal of Engineering Education Vol 3, No 2 (2021)
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijee.3.2.%p

Abstract

Nowadays medical imaging systems tend to have the greatest impact on disease identification, diagnosis, and surgical preparation. At the same time, compression of image avoids data redundancy, reduces bandwidth, etc. This makes the system more peculiar in this field. Three main steps are being used in the proposed paradigm: (a) segmentation, (b) image compression, and (c) image decompression. Image segmentation is the first step, which is attained by the Optimized Active Contour Model (OACM). Using a new Modified marriage in honey bees optimization model (MMBO), the weighting factor and maximum iteration of ACM are fine-tuned. Thereby, the collected input image is differentiated or segmented into two: N-ROI and ROI, respectively. The ROI marked field will indeed be encoded using ISPIHT based lossy compression model, whereas the non-ROI area is encoded using DCT based lossy compression model. In terms of BSC, the outcomes from both the ISPIHT algorithm and the DCT model are merged and the compressed image is its output. Following that, the compressed image will then be subjected to image decompression. This will include bit-stream segregation, which will be processed separately for the ROI and non-ROI regions using both ISPIHT decoder and DCT based decomposition. This process results in the original image. Finally, a comparative evaluation is undergone between the proposed and the existing techniques in terms of PSNR, SSIM, and CR as well.
Analysis on Quality of Learning in e-learning Platforms Veeramanickam Murugappan M.R; Rajakumar B R; Binu D; Ramesh P.
International Journal of Engineering Education Vol 3, No 2 (2021)
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijee.3.2.%p

Abstract

This paper plans to introduce a model that concerns on e-learning quality management system under two phases: (i) Questionnaire preparation and (ii) Predicting the impact of e-learning quality. In order to analyze the quality of learning in e-learning platform, initially, the questionnaire will be prepared with respect to various drivers such as (i) Degree of flexibility and adaptability, (ii) Degree of supportability (students and staffs) (iii) Staff qualification and experience, (iv) Performance assessment and (v) Learner’s interest. The first driver includes factors like learner control, learner activity, motivation and feedback. The second driver includes factors like technical skills, cost and technical crisis and internet access. The third driver includes factors like awareness of new technology, whether the team includes instructional designers, multimedia procedures and so on. The fourth driver (Performance assessment) includes the impact of performance evaluation by means of Artificial Intelligence (AI) methods. The fifth driver includes factors like course materials, gaming and learners self interest. The prepared questionnaire is distributed to different age group people and are demanded to fill up the precise information as much as possible. These responses from the people are then taken for analysis purpose. In this research work, the analysis is carried out based on SEM analysis, which is a way to identify the learning quality in e-learning platform.
Co-Authors Abhishek Bhatt Binu D Rajasekhar Butta Ramesh P. Shabanam Shabbir Tamboli Veeramanickam Murugappan M.R