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Cloud Computing in Enhancing the Efficiency and Integration of Alternative Energy Systems 2

Cloud Computing in Enhancing the Efficiency and Integration ...

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2nd International Conference on Computational Intelligence, Communication technology and Networking, CICTN 2025

作者： Sahoo, Amiya Kumar Prusty, Sucharita Jayasingh, Suvendra Kumar Swain, Asish Kumar Mohanta, Hemanta Kumar Aryan Institute of Engineering and Technology Odisha Bhubaneswar India Institute of Management and Information Technology BPUT Odisha Cuttack India

ISBN: (纸本)9798331530389

In response to growing environmental concerns and the need for sustainable development, alternative energy systems have emerged as crucial solutions to the problems associated with fossil fuels. This research focuses on the significant role cloud computing plays in improving the efficiency and integration of various alternative energy systems such as solar, wind, hydropower, biomass, geothermal, and tidal/wave energy. The study explores how cloud computing technologies enable real-time data processing, storage, and analysis of the large datasets generated by these renewable energy sources, thus optimizing their performance and integration into the energy grid. Cloud computing provides advanced data management tools that are vital for managing the variable and intermittent nature of renewable energy production. By utilizing cloud-based platforms, energy producers can achieve improved forecasting, load balancing, and energy distribution, which are essential for enhancing efficiency and reliability. Additionally, this research highlights how cloud computing fosters collaboration and innovation by offering a scalable and flexible infrastructure. This infrastructure supports the development of new technologies and applications within the renewable energy sector, promoting continuous advancements and breakthroughs. This research underscores the crucial role of cloud computing in advancing a sustainable energy future. © 2025 IEEE.

关键词： Cloud platforms

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Present Knowledge on Pre-processing of Phosphogypsum as a Building Material

Present Knowledge on Pre-processing of Phosphogypsum as a Bu...

引用

National Conference on Technological Advancements in Waste Management: Challenges and Opportunities, TAWMCO 2023

作者： Jaiswal, Sunny Acharya, Prasanna Kumar Pati, Rajalaxmi Kapri, Biswajit School of Civil Engineering Kalinga Institute of Industrial Technology Odisha Bhubaneswar India Aryan Institute of Engineering and Technology Odisha Bhubaneswar India

ISBN: (纸本)9789819760237

Due to its extensive production and disposal problem, phosphogypsum (PG), a byproduct of the phosphate fertilizer industry, poses serious environmental issues. An estimated 200–300 million tons of phosphogypsum are produced annually;of these, 58% are either dry- or wet-stacked, 28% are discharged into coastal waters, and only 14–15% are directly recycled, primarily as raw materials for construction projects, fertilizers, and soil stabilization techniques. When phosphogypsum is used in infrastructures, there are concerns about the environmental effects because it contains harmful materials such as heavy metals and radioactive chemicals. To lessen the negative effects of phosphogypsum on the environment, this article summarizes treatment techniques, with particular emphasis on approaches for the material's efficient use as a building material and secure disposal. The treatment options discussed in this paper include physical processes such as dewatering and solidification, chemical treatments for contaminant removal, and innovative approaches like encapsulation and conversion into useful products. The study explores the potential of several treatment approaches, emphasizing the value of sustainable phosphogypsum management approaches. This survey highlights the need for ongoing research and development in this field to promote resource utilization and environmental protection. It also offers insightful information about the current state of phosphogypsum treatment technologies through a thorough analysis of existing research and case studies. The study revealed that the physical approaches employed for the preprocessing in removing the impurities of phosphogypsum are easy and inexpensive. The calcination process for the same requires huge energy and emits Carbon dioxide. However, the calcination period and temperature can be lowered with the application of chemicals. It is also learned that a small amount of Portland cement can activate the contaminants in phosphogyps

关键词： Phosphate fertilizers

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Machine Learning For Smart School Selection And Admissions

Machine Learning For Smart School Selection And Admissions

引用

2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Gupta, Anish Tyagi, Lalit Kumar Kumar, Sandeep Chandigarh Group of Colleges Chandigarh Engineering College Department of Computer Science & Engineering Mohali India Aryan Institute of Technology Ghaziabad India

ISBN: (纸本)9798331508685

Selecting the appropriate school for their child is one of the decisions that parents are faced with in life, this process can be stressful and uncertain at times. Thus, machine learning is noted to be a possible solution that can be deployed to enhance and optimize the admissions and school selection process in the current periods. The aim of this research is to explore the framework and applicability of machine learning techniques in view of selective admissions, and smart school selection. In the early stages of our investigation, we suggest a simple to use, web based tool where with the aid of different learning machines, all the parents and guardians will be able to find the appropriate school for their child. To help the clients to select particular schools, the website collects and consolidates various information including, but not limited to the following: season activity involvement, academic performance, geographical preferences, and school ranking. This makes the process of selecting a school to attend easier and also helps parents to make right decisions for their children to attend the best school. The second section of this paper describes the procedures of implementing the machine learning techniques in detail, the overviews of the steps of feature selection, data preprocessing, and model evaluation. We also point out the challenges and ethical concerns of employing machine learning for school choice and the problem of an objective machine over a bias one. © 2025 IEEE.

关键词： Adversarial machine learning

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AI-based Learning Techniques for Bladder Cancer Detection

AI-based Learning Techniques for Bladder Cancer Detection

引用

2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Kumar, Sandeep Saurabh Aggarwal, Ankita Aryan Institute of Technology Ghaziabad India Chandigarh Group of Colleges Chandigarh College of Engineering Department of Computer Science & Engineering Mohali India Chandigarh Group of Colleges Chandigarh Engineering College Department of Electronics & Communication Engineering Mohali India

ISBN: (纸本)9798331508685

There is no doubt that the main issue to address in these patients is the early diagnosis of Bladder carcinoma. This work aims at initiating a new path in this research and undertakes advanced artificial intelligence (AI) and machine learning to enhance bladder cancer diagnosis. Bladder cancer is one of the more widespread malignant neoplasms, it is more prevalent in the male population and particularly in male gerontocracy. Conventional diagnostic approaches are hypertrophied and crippled by constraints that lead to diagnostic imperfections and unkind lateness. There stands a great opportunity to deal with these challenges through the implementation of Artificial Intelligence in healthcare. By incorporating the modern artificial intelligence models such as CNN and RNN along with other modern techniques, this research intends to improve the diagnostic outcomes and provide strong prognosis. It is through a comprehensive method of data preprocessing and feature engineering, an incorporation of ethical factors, and the use of complex algorithms that this research hopes to advance the future of precision medicine. In this context, the customized solutions based on the most effective data also expand the scope of the diagnosis of bladder cancer and bring positive changes to the treatment of patients. © 2025 IEEE.

关键词： Diseases

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Cloud Computing in Enhancing the Efficiency and Integration of Alternative Energy Systems

Cloud Computing in Enhancing the Efficiency and Integration ...

引用

Computational Intelligence, Communication technology and Networking (CICTN), International Conference on

作者： Amiya Kumar Sahoo Sucharita Prusty Suvendra Kumar Jayasingh Asish Kumar Swain Hemanta Kumar Mohanta Aryan Institute of Engineering and Technology Bhubaneswar Odisha India Institute of Management and Information Technology BPUT Cuttack Odisha India

ISBN: (数字)9798331530389

ISBN: (纸本)9798331530396

关键词： Cloud computing Renewable energy sources Technological innovation Collaboration Production Data processing Real-time systems Security Reliability Sustainable development

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ICOA Based Load Frequency Control Optimized ITDF Controller Integrating Distributed Generation Resources 3

ICOA Based Load Frequency Control Optimized ITDF Controller ...

引用

3rd IEEE International Conference on Industrial Electronics: Developments and Applications, ICIDeA 2025

作者： Pahadasingh, Sunita Nayak, Pratap Chandra Panda, Ajit Kumar Jena, Chitralekha Panda, Babita Aryan Institute of Engineering & Technology Dept. of Electrical Engineering Bhubaneswar India School of Electrical Engineering KIIT University Bhubaneswar India

ISBN: (纸本)9798331533205

The load frequency control of a multi-area system integrated with distributed generation resources are applied in this study using improved coati optimization algorithm (ICOA). Wind turbines' intermittent power output under frequent and economical load adjustments in distributed generation resources (DGR) contributes to tie-line power instability and system frequency ambiguity. Review the current electricity system's performance going forward, taking into account the integrated DG resources. A revolutionary integral of tilted derivative filter (I-TDF) controller is explored using ICOA for enhancement of frequency stability. Research shows that I-TDF performs better than other controllers in terms of lowering peak, settling time, and cost function value. The ICOA algorithm's superiority is contrasted with that of the sine cosine algorithm (SCA) and emperor penguin optimization (EPO). © 2025 IEEE.

关键词： Cost functions

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ICOA Based Load Frequency Control Optimized ITDF Controller Integrating Distributed Generation Resources

ICOA Based Load Frequency Control Optimized ITDF Controller ...

引用

Industrial Electronics: Developments & Applications (ICIDeA), IEEE International Conference on-

作者： Sunita Pahadasingh Pratap Chandra Nayak Ajit Kumar Panda Chitralekha Jena Babita Panda Dept. of Electrical Engineering Aryan Institute of Engineering & Technology Bhubaneswar India School of Electrical Engineering KIIT University Bhubaneswar India

ISBN: (数字)9798331533205

ISBN: (纸本)9798331533212

关键词： Sensitivity analysis Reviews System performance Power system management Power system stability Cost function Stability analysis Distributed power generation Wind turbines Frequency control

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Design of a Solar-Powered Remote-Controlled Aquatic Cleaning Drone 3

Design of a Solar-Powered Remote-Controlled Aquatic Cleaning...

引用

3rd IEEE International Conference on Industrial Electronics: Developments and Applications, ICIDeA 2025

作者： Nandi, Mayukh Panda, Babita Jena, Chitralekha Pahadsingh, Sunita Kumar, Ankit Mandal, Soumyadip Singhania, Devashish School of Electrical Engineering KIIT Deemed to be University Bhubaneswar India Aryan Institute of Engineering & Technology Department of Electrical Engineering Bhubaneswar India

ISBN: (纸本)9798331533205

The Remote-Controlled Solar Lake Pool Cleaner Drone is an innovative solution designed to automate the cleaning process of large bodies of water, such as lakes and pools, using renewable solar energy. This drone combines the advantages of remote control functionality, efficient cleaning mechanisms, and environmentally friendly power sources to provide an effective and sustainable solution for maintaining water cleanliness. The drone is equipped with advanced cleaning mechanisms, including a suction system and a brush mechanism, capable of efficiently removing debris, leaves, and algae from the water surface. Its remote-control capabilities allow operators to maneuver the drone effortlessly, enabling precise navigation and targeting specific areas requiring cleaning. © 2025 IEEE.

关键词： Remote control

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Design of a Solar-Powered Remote-Controlled Aquatic Cleaning Drone

Design of a Solar-Powered Remote-Controlled Aquatic Cleaning...

引用

Industrial Electronics: Developments & Applications (ICIDeA), IEEE International Conference on-

作者： Mayukh Nandi Babita Panda Chitralekha Jena Sunita Pahadsingh Ankit Kumar Soumyadip Mandal Devashish Singhania School of Electrical Engineering KIIT Deemed to be University Bhubaneswar India Department of Electrical Engineering Aryan Institute of Engineering & Technology Bhubaneswar India

ISBN: (数字)9798331533205

ISBN: (纸本)9798331533212

关键词： Renewable energy sources Solar energy Lakes Cleaning Water pollution Safety Rivers Water resources Robots Drones

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Machine Learning For Smart School Selection And Admissions

Machine Learning For Smart School Selection And Admissions

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Pervasive Computational Technologies (ICPCT), International Conference on

作者： Anish Gupta Lalit Kumar Tyagi Sandeep Kumar Department of Computer Science & Engineering Chandigarh Engineering College Chandigarh Group of Colleges Mohali India Aryan Institute of Technology Ghaziabad India

ISBN: (数字)9798331508685

ISBN: (纸本)9798331519476

关键词： Ethics Data analysis Computational modeling Decision making Education Data preprocessing Machine learning Feature extraction Data models Recommender systems

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