Author details
Author's Published Works
Author details
Showing 1-9 of 9 results
- Sort
Filter Results
Show
Sort By
Results
Overcoming Distortion and Residual Stress Challenges in Wire Arc Additive Manufacturing through Advanced Process Control
Hussein Oraibi Hawi Al Zaidi;S Vinod Kumar;Vijilius Helena Raj;Sorabh Lakhanpal;Dinesh Kumar Yadav;K. Neelima
2024 OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 4.0
Year: 2024 | Conference Paper |
Wire Arc Additive Manufacturing (WAAM) has emerged as a transformative technology in the field of additive manufacturing, offering the potential for rapid, cost-effective, and large-scale production. This paper presents a comprehensive framework for optimizing and controlling various aspects of WAAM, addressing challenges such as distortion and residual stress. The proposed methodology comprises f...Show More
Machine Learning-Enhanced Blockchain Solutions for Sustainable Energy Consumption and Carbon Footprint Tracking
Sorabh Lakhanpal;S Vinod Kumar;Vijilius Helena Raj;Garima Yadav;Dinesh Kumar Yadav;Mohammed Q. Saadoon
2024 OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 4.0
Year: 2024 | Conference Paper |
This study looks at what blockchain technology and machine learning can do to help achieve optimal energy use and monitor carbon footprints. A method that combines federated learning with LSTM has been presented to give a real-time perspective of energy use. Furthermore, an immutable blockchain record is now accessible to publicly document carbon emissions. To achieve the above indicated goals, bo...Show More
Benign Non-Convex Optimization Techniques for Training Neuro-Inspired Architectures
Vandana Roy;S Vinod Kumar;Vijilius Helena Raj;Sorabh Lakhanpal;Dinesh Kumar Yadav;Rafil A. Alzuhairi
2024 OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 4.0
Year: 2024 | Conference Paper |
In non-convex optimization contexts, neuronal network optimization is difficult yet crucial. The novel Adaptive Ensemble of Benign Non-Convex Optimization Algorithms (ABNOA) improves neuron-inspired structure training. SGD is trapped in local minima when there are non-convex loss surfaces; therefore, it doesn’t always work. ABNOA solves these issues by dynamically selecting, combining, and fine-tu...Show More
Implicit Bias Analysis in The Training of Compact Neural Networks For Inverse Problems
Uma Reddy;S Vinod Kumar;Aakriti Yadav;Amandeep Nagpal;Ashwani Kumar;Nashat Ali Soud
2024 OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 4.0
Year: 2024 | Conference Paper |
This paper suggests three new techniques to improve tiny neural networks’ inverse problem-solving. Traditional approaches, like basic linear regression models, lack the flexibility and bias reduction needed to handle complex real-world challenges. Our recommended methods—BRT, ABN, and LFD—can solve these issues. The BRT technique balances bias reduction with data fitting by using L1 and L2 regular...Show More
Next-Generation Artificial Intelligence Solutions for Comprehensive Analysis and Improvement of Heat Dissipation in High-Intensity Boiling Environments
H. Manoj T. Gadiyar;S Vinod Kumar;Vijilius Helena Raj;Dinesh Kumar Yadav;Mortada Kareem Sabi Hasoni;Sorabh Lakhanpal
2024 OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 4.0
Year: 2024 | Conference Paper |
This research delves into the realm of AI-driven heat dissipation, offering a suite of algorithms to address the challenges posed by high-intensity boiling environments. The proposed predictive modeling algorithm, rooted in linear regression, provides a systematic and robust approach through 20 meticulously designed steps. This algorithm, along with neural networks, reinforcement learning, generat...Show More
Human-Machine Interaction Systems for Training Industrial Robots
S Vinod Kumar;Dinesh Mishra;Uma Reddy;Amandeep Nagpal;Ashwani Kumar;Zahraa Saad Al-Asadi
2024 OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 4.0
Year: 2024 | Conference Paper |
Workplace robot processing speed and efficiency depend on human-machine interaction. This study investigated RLIL, ViTREX, and NLCCF, three innovative HMI approaches. The purpose is to improve workplace robot setup and use. RLIL uses copying and reinforcement learning to improve robot behaviour in real time. Workshops and assembly lines benefit from this flexible and precise solution. Computer vis...Show More
Exploring Advanced Techniques in Computer and Network Forensics for Enhanced Cybersecurity
Amandeep Nagpal;S Vinod Kumar;Uma Reddy;K. Radha;Ashwani Kumar;Namaat R. Abdulla
2024 OPJU International Technology Conference (OTCON) on Smart Computing for Innovation and Advancement in Industry 4.0
Year: 2024 | Conference Paper |
Because cybersecurity is continually changing, it’s crucial to have effective, adaptable defenses. This paper demonstrates a novel computer security method. This is done via blockchain technology, enhanced cryptography, threat intelligence integration, machine learning-based strangeness detection, and behavioral analysis. After carefully comparing our solution to others, we feel it is the best way...Show More
Leveraging Graph Neural Networks for Complex Network Traffic Signal Processing
S Vinod Kumar;Anurag Shrivastava;Aravinda K;Lavish Kansal;Ravi Kalra;Hawraa Ali Sabah
2024 International Conference on Trends in Quantum Computing and Emerging Business Technologies
Year: 2024 | Conference Paper |
With the development of deep learning algorithms, automated interpretation has advanced significantly, but simultaneous interpretation of speech and sign language still presents a major obstacle. In order to close the communication gap between the hearing and the deaf populations, this study offers novel multimodal deep learning techniques for the simultaneous interpretation of speech and sign lan...Show More
Machine Learning-Enhanced Predictive Control for Modular Multilevel Converters in HVDC Transmission Systems
S Vinod Kumar;Sujin Jose Arul;Lavish Kansal;Ravi Kalra;Koushal Dhamija;Adnan Allwi Ftaiet
2023 International Conference on Power Energy, Environment & Intelligent Control (PEEIC)
Year: 2023 | Conference Paper |
Modular Multilevel Converters (MMCs) are pivotal components in High Voltage Direct Current (HVDC) transmission systems, underpinning the advancement of contemporary power grids. Their operational efficiency and reliability are of paramount importance for the stability of interconnected networks. Traditional control methodologies, although robust, often fall short in swiftly adapting to dynamic gri...Show More
IEEE Account
Purchase Details
Profile Information
Need Help?
- US & Canada: +1 800 678 4333
- Worldwide: +1 732 981 0060
- Contact & Support
- About IEEE Xplore
- Contact Us
- Help
- Accessibility
- Terms of Use
- Nondiscrimination Policy
- Sitemap
- Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.