Notice Board :

Call for Paper
Vol. 12 Issue 9

Submission Start Date:
September 01, 2025

Acceptence Notification Start:
September 10, 2025

Submission End:
September 20, 2025

Final MenuScript Due:
September 28, 2025

Publication Date:
September 30, 2025
                         Notice Board: Call for PaperVol. 12 Issue 9      Submission Start Date: September 01, 2025      Acceptence Notification Start: September 10, 2025      Submission End: September 20, 2025      Final MenuScript Due: September 28, 2025      Publication Date: September 30, 2025




Volume XII Issue VIII

Author Name
Dr. Kshamasheel Mishra, Dipanti Marothiya
Year Of Publication
2025
Volume and Issue
Volume 12 Issue 8
Abstract
As the digital economy expands, the environmental impact of cloud computing becomes increasingly significant. This paper explores the intersection of cloud technology and sustainability, proposing frameworks and strategies to mitigate the ecological footprint of digital operations. We investigate current practices in cloud infrastructure, highlight successful case studies, and present recommendations for businesses and policymakers. Ultimately, we advocate for a collaborative approach to harness the power of cloud computing for environmental good.
PaperID
2025/IJTRM/08/2025/45865

Author Name
Dr. Rizwana Parveen
Year Of Publication
2025
Volume and Issue
Volume 12 Issue 8
Abstract
Visual information transmitted through digital images has emerged as a significant method of communication in contemporary society; however, the images often suffer from corruption due to noise during transmission. Consequently, these images require processing to achieve usability in various applications. Image denoising refers to the techniques used to manipulate image data in order to create visually high-quality images. This denoising process employs various methods, including wavelet transformation, Wiener filter, and mean filter, all of which are implemented using MATLAB. For comparative analysis of these image denoising techniques, input images such as the Barbara, Cameraman, and House images were utilized. The proposed method demonstrated superior performance compared to existing approaches, indicating its effectiveness in producing cleaner, higher-quality images.
PaperID
2025/IJTRM/08/2025/45866