The cryptanalysis of multimodal datasets is particular, given the distinct statistics formats and cryptographic strategies that pose demanding situations to analysis. In this studies paintings, an green cryptographic algorithm for boosting the robustness and accuracy of cryptanalysis the usage of deep mastering is proposed. This method includes the usage of CNNs and transformer-based totally architectures in a systematic evaluation of multimodal datasets along with textual content, pictures, and numerical statistics to pick out the cryptographic styles and vulnerabilities. The model consists of feature extraction, modality fusion, and automated key inference to decode encrypted information with progressed efficiency.

Keywords : Kidney disease classification, CT images, CNN- LSTM, Deep learning, Grad-CAM, Medical imaging.

Author : M. Pavan , S. Dilli Babu

Title : An Effective Cryptographic Algorithm For Multimodal Datasets Cryptanalysis Using Deep Learning

Volume/Issue : 2025;2(4)

Page No : 1 - 7

The current study article examines the growing use of automation and Artificial Intelligence (AI) in enterprises' diverse human resource roles. The process of improving the HR department's efficiency through human resource automation involves relieving staff members of time-consuming manual activities so they can concentrate on more complicated responsibilities like decision-making and strategy-making. Technology like artificial intelligence is defining modern paradigms for conducting business. It is a solution that completes the majority of low-value HR tasks so that the strategic scope of work can receive more attention. Artificial intelligence is most frequently used in human resource applications like hiring and onboarding, internal mobility and employee retention, and task automation. HR professionals may expedite candidate vetting with the help of AI. By employing more user-friendly forms and experiences that draw higher talent and guarantee that interested parties complete their applications, adopting AI tools improves the application process for candidates as well. This research work is based on concepts and descriptive analysis. This research study used secondary data from recent research articles that were found on search engine websites. The study is an effort to recognize the important role AI has played in improving organizational decision-making. AI has the potential to improve HR departments in a number of ways. Employing AI may assist HR managers in a number of ways, including keeping up with trends; analysing employee sentiment; streamlining talent acquisition and onboarding; and spotting patterns to make decisions. HR will take on more strategic roles and become more data-driven. For HR professionals who are eager to keep up with the pace ,the technology reckoning can open up a whole new chapter. This observation will assist policymakers in understanding the advantages and importance of implementing AI in human resource management.

Keywords : Artificial intelligence, Automation, Human Resource Management, HR Professionals, Technology

Author : S. Shaheera Bhanu

Title : Revolutionizing Human Resources through Artificial Intelligence and Automation

Volume/Issue : 2025;2(4)

Page No : 8 - 11

This paper introduces an innovative solution to water pollution through the development of a remote-controlled floating waste cleanup system. Designed to autonomously collect floating waste from water bodies, the system minimizes human intervention while ensuring safe and efficient operations. It incorporates a belt-driven waste collection mechanism that continuously gathers debris into a designated collector bin, powered by a battery charged via a solar panel to promote sustainable energy use. The cleanup vessel is equipped with an ESP32-CAM module that enables live video streaming for real-time remote monitoring, allowing operators to oversee the cleaning process effectively. An integrated ultrasonic sensor measures the fill level of the collector bin, providing essential feedback to ensure timely waste disposal. Additionally, a web-based dashboard offers wireless control, enabling operators to manoeuvre the vessel in multiple directions—forward, reverse, left, and right, while managing the activation of the conveyor belt. Overall, this system not only improves the efficiency of water surface cleaning but also reduces the risks and labor associated with manual cleanup operations. It demonstrates a scalable, environmentally friendly solution for maintaining cleaner aquatic environments through the integration of automated control, renewable energy, and real-time monitoring technologies

Keywords : Floating Waste Cleanup, ESP32-CAM, Conveyor Belt, Water Pollution, Renewable Energy.

Author : M. Revathy , M. Yaswanth Maruthi Pritam , B Thasneem , M. Neelima , S. Fatheema

Title : Remote Controlled Floating Waste Cleanup System

Volume/Issue : 2025;2(4)

Page No : 12 - 17