The Department of Computer Science and Engineering is glad to announce that Assistant Professor Dr Saleti Sumalatha and her students got two of their patent applications published in a row. The patent titled “System and method for mining of constraint based high utility time interval sequential patterns” (Application number: 202241044001) was published in collaboration with the BTech students; K Rasagna, N Naga Sahithya, K Hemalatha, B Sai Charan, and Upendra Karthik.

The main intention of the proposed system is to discover the sequences that include the time period between the purchases of each item. For example, if we consider a shop which sells some groceries like Grains, Milk, Yogurt, Bread and Eggs as the set of items in the database. Now, the main aim is to find the time period between the purchases of particular items that are being sold. From this, the shop owner can easily maintain the stock of completed items according to the time period.

For example, an output sequential pattern including time intervals of the form indicates that a customer who purchased item x also bought item y after three months and visited the store again after five months to buy item z. It considers the same utility threshold for each of the items in the database, which shows that each item is assumed to have the same unit profit. This is not convincing as each item is different in real-time applications and should not be treated equally. For example, the sales of” Gold bangles” will produce more profit than the sales of” Cotton Jeans”. In view of this, the research proposes UIPrefixSpan-MMU.

The other patent titled “A system and a method for automatic essay grading” (Application number: 202241043045) was published in collaboration with M Purnima, G Haveela, K U Meghana, and S Deepthi Reddy. Essay grading systems are being adopted by different organisations to reduce the hectic workload from a teacher’s point of view. They made a model which is trained with datasets containing different essay topics and numerous essays with scores varying in a wide range.

Essay grading systems will not only save the time for evaluation but also give accurate results. The output of the system will be quick such that it could evaluate many essays and get trained. This system benefits both the student and the teacher as well. Their model predicts the scores of the essay by comparing them with the features extracted from the trained data. This model can be used to reduce the effort of teachers to grade many essays in a limited time. The work of grading will be fastened and accurate.

The research team from the Department of Computer Science and Engineering proposes a research scheme to address security concerns in the transmission of digital images of aerial Remote sensing images over the Internet. Assistant Professor Dr Priyanka, Assistant Professor Dr Jatindra Kumar Dash, research scholar Ms K Jyothsna Devi, and BTech student Mr. M V Jayanth Krishna, published the paper A New Robust and Secure 3-Level Digital Image Watermarking Based on G-BAT Hybrid Optimization in the Mathematics Journal SCI, a Q1 Journal with an Impact Factor of 2.9. The research project combats various threats in the transmission of Remote sensing images, such as copyright protection, copy control, and unauthorized access.

Abstract

This contribution applies tools from the information theory and soft computing (SC) paradigms to the embedding and extraction of watermarks in aerial remote sensing (RS) images to protect copyright. By the time 5G came along, Internet usage had already grown exponentially. Regarding copyright protection, the most important responsibility of the digital image watermarking (DIW) approach is to provide authentication and security for digital content. The main goal of the paper is to provide authentication and security to aerial RS images transmitted over the Internet by the proposal of a hybrid approach using both the redundant discrete wavelet transform (RDWT) and the singular value decomposition (SVD) schemes for DIW. Specifically, SC is adopted in this work for the numerical optimisation of critical parameters. Moreover, 1-level RDWT and SVD are applied to digital cover images and singular matrices of LH and HL sub-bands are selected for watermark embedding. Further selected singular matrices S LH and S HL are split into 3 × 3 non-overlapping blocks, and diagonal positions are used for watermark embedding. Three-level symmetric encryption with a low computational cost is used to ensure higher watermark security. A hybrid grasshopper–BAT (G- BAT) SC-based optimization algorithm is also proposed to achieve high-quality DIW outcomes, and a broad comparison against other methods in the state-of-the-art is provided. The experimental results have demonstrated that the proposal provides high levels of imperceptibility, robustness, embedding capacity, and security when dealing with DIW of aerial RS images, even higher than the state-of-the-art methods.

The proposed scheme is easily dumped into the sender and receiver machines to work readily. MATLAB platform is the only requirement. Researchers aspire to design new image watermarking schemes using machine learning and deep learning techniques. For this project, they have collaborated with Professor José Santamaría from the Department of Computer Science, University of Jaén, and Professor Antonio Romero-Manchado from the Department of Cartographic Engineering, Geodesy, and Photogrammetry, University of Jaén.