Synthesis and characterisation of magnesium-doped nanoparticles by the microwave combustion technique for novel applications Sivaraman Baskar, Sivaraman Kanithan, Natarajan Arun Vignesh, N. Santhosh, Faisal M. Alfaisal, Shamshad Alam, Hasan Sh. Majidi, Sameer Algburi, Osamah J. Al-sareji Materials Science Poland, 2025 In this study, synthesis and characterisation of magnesium-substituted Ni–Fe nanoparticles using microwave combustion are carried out. Using Schererr’s formula, the crystal size of the synthesised magnesium-substituted Ni–Fe nanoparticles is determined, which falls between 18 and 32 nm. Additionally, agglomerative spherical-shaped nanoparticles have been observed by high-resolution scanning electron microscopy investigation, and energy-dispersive X-ray spectroscopy is used to determine the elemental composition of Mg, Ni, Fe, and O. With the aid of diffuse reflectance spectroscopy, band gap values for the produced samples are determined to fall between 3.35 and 2.32 eV. Metal–oxygen tetrahedral sites are represented by the absorption band at 583 cm−1, while octahedral sites are linked to the absorption bands at 436 and 457 cm−1. The nickel ferrite nanoparticles being replaced with magnesium show ferromagnetic hysteresis curves.
Performance Improvement and Optimization of Nanomaterial-Based Liner Materials for 3D-IC Integration Santosh Kumar Tallapalli, V. Vijayakumar, Asisa Kumar Panigrahy, N. ArunVignesh 2025 IEEE International Conference on Emerging Technologies and Applications Mpsec Iceta 2025, 2025 Several technological advancements have been made owing to the growth of IC. Devices are used daily, and, as a result, they have significantly impacted lives and existence, which would be incomprehensible without them. As a result, the reliability issues associated with recent devices necessitate extraordinary, specialized efforts. Accommodating several devices in a single and planar IC leads to various system-level damages to the IC, like the hot carrier effect, oxide breakdown, etc. This paper examines optimization strategies to improve the performance of nanomaterial-based liner materials in noise coupling sustainability. It also gives a complete defect analysis of those materials through electrical interventions. Active devices in one IC are integrated through another IC via vertical bonding. Electrical interference with nearby Through Silicon Vias (TSVs) and operational transistors is a major issue when implementing 3D IC, since it significantly lowers system efficiency. This study provides an innovative way to reduce electrical interference by utilizing several electrical interference designs, which include the TTSV framework, which also incorporates Thermal TSV while simulation, and the ETSV framework, which solely utilizes electrical signal carrying TSV. The study examined the electrical intervention of TSV-carrying signals to the substrate and other TSV. Additionally, using several suggested designs, this work shows further elevated frequency regimes up to 1 THz. Our simulation result suggests the proposed model has a marginal advantage in 3D IC developments with more than a $30 \%$ drop in electrical signal intervention from signal-carrying TSV to other TSV. Additionally, a guard ring was used to demonstrate electrical interference. When Teflon AF1600 liner material was used at the victim along with a P+ protection ring, TSV demonstrated very little electrical interference.
Self-Healing Data Pipelines: Reinforcement Learning for Real-Time Fault Detection and Autonomous Recovery Kasarla Priyanka, S. Priyadharshini, N Arun Vignesh, Ammar Hameed, Ranjith Reddy K, Praveenkumar C 2025 International Conference on Metaverse and Current Trends in Computing Icmctc 2025, 2025 For resilience and reliability of modern data-driven applications, self-healing data pipelines are necessary. Current technique of fault detection and recovery is usually implemented using traditional static rule-based approaches, which are not able to adjust to the changing data environment. In this research, a new reinforcement learning (RL) based self healing data pipeline that detects and classifies faults in the data pipeline and recovers itself in real time is proposed. To dynamically optimize the fault mitigation strategies, we propose the framework to integrate the deep Q networks (DQN) and proximal policy optimization (PPO) as long as a self-supervised anomaly detection module enhances the real-time fault prediction. Also, a meta learning component, by using model agnostic meta learning (MAML), speeds up adaptation to unseen failures. Generative adversarial networks (GANs) are used by the system, without human intervention, to autonomously select the optimal actions for recovery under data routing, schema adaptation, and replacement of missing data. Experimental results show that RL based self-healing pipeline is more accurate than traditional methods, completes recovery faster, and delivers better quality of services. It also supports scalable deployment to cloud and edge environment for robust data pipeline management in a distributed system. This research presents a self-evolving AI-based solution to continue to keep the data processing flowing at a steady pace and without human intervention, maintain real-time fault resilience, and continuous operational efficiency as close to a seamless environment as possible.
Novel Smart Mountable Cooling Pad Using Type C Silica Gel Balambigai Subramanian, Arun Vignesh N, Sarankumar R, Sivaram Krishnan M, Vennila A, Prawinraj G 2025 International Conference on Computational Innovations and Engineering Sustainability Iccies 2025, 2025 Life without mobile phone is inevitable in this modern day of living. Mobile is a communication device which connects people from any part of the world and makes them feel that the person is right here. Mobile is a device which brings the world in the users hand. Mobile phone is an electronic device which becomes heated over a certain period of time after usage. Heating of mobile phones has various effects on the internal circuits of mobile phone. This also affects CPU, chipsets, integrated circuits, graphics card and also other various parts of the mobile. Heating of mobile phones is the main disadvantage and issue from the customer in the modern world. Many top companies have used various techniques and mechanism to overcome this issue. Many methods include air cooling method, liquid cooling method, vapour cooling method, they are inbuilt in the upcoming mobiles, but the cooling mechanism of these methods doesn’t maintain the temperature of the mobile phone within the certain permissible temperature. To overcome this issue, a design is developed which includes a semiconductor cooling technology along with 3-D printing to maintain the temperature. This method involves five layers which includes silica gel sheet, thermal sheet, semiconductor cooling pad, cooling column and a fan. All these layers are mounted in a single device which is designed using 3-D printing technology. This cooling system is portable, adjustable and mountable semiconductor cooling system. This method involves a fan of 10,000 rpm, Type-C silica gel which is a macroporous substance which helps in rapid cooling and maintaining the temperature of the mobile. Due to this methodology, the effects of heating like decreased phone performance, battery degradation, shortening of lifespan of the device, melting of integrated circuits and in worst cases this may also lead to explosion of the mobile. The usage of this 3-D printed cooling device reduces the temperature of mobile by an average of 8 F and maintain the temperature of the mobile. The average temperature of the mobile phone after using it for an hour is displayed as 112 F in the thermal gun, by using this device for a minute the average temperature of the mobile phone is reduced significantly to 96.1 F. The temperature of the mobile phone is reduced as an average of 6%. This mountable device will be evolved in the future with inbuilt cooling system or either cooling case by automatically measuring the temperature and it is charged with wireless charging mechanism.
Design of Rectangular Micro-strip Patch Antenna using CST Manisha Reddy Duddukunta, Bhavith Yadav Katikireddy, Shiva Praneeth Reddy Bembadi, N Arun Vignesh, K Swaraja 2024 3rd International Conference on Artificial Intelligence for Internet of Things Aiiot 2024, 2024 In the Industrial, Scientific, and Medical (ISM) band (2.45 GHz), rectangular micro-strip patch antenna (RMPA) is simulated and its performance is analyzed in this study. High gain, broad bandwidth, and small size antennas that can provide improved performance over a wide variety of frequency spectrum as are developed over a Flame Retardant-4 (FR-4) substrate are required by the latest mobile communication systems. In order to obtain both compact dimensions and optimal parameters like high radiation efficiency, high gain, and resonating frequency—the antennas’ optimal design parameters are chosen. Antenna parameters like return loss, gain, and width as well as dimensions like length (L), width (W), and substrate dielectric are calculated by CST software. The antenna is intended to operate between 2 and 2.5 GHz. For this reason, this antenna is ideal for use in medical settings. The constructed antenna’s simulated results are obtained with CST Microwave Studio, and micro strip inset feed is employed. Impedance matching employs a micro-strip line feed due to its simplicity in construction, the ease of achieving a match by altering the inset position, and its straightforward modelling process.
Design and Analysis of Helical Antenna for GPS Systems Mahendar Bandi, Sathvik Chintakunta, Sreeja Sri Raja Raghava Raju, N Arun Vignesh, K Swaraja 2024 3rd International Conference on Artificial Intelligence for Internet of Things Aiiot 2024, 2024 The primary objective of designing a helical antenna tailored for GPS-based systems. The antenna is tuned to the GPS frequency (3010MHz) and exhibits optimized parameters critical for better performance. The helix dimensions, including pitch angle (0.2 times the wavelength) and diameter($3.17 \\mathrm{~cm})$, are carefully chosen to influence the radiation pattern (circularly polarized omnidirectional), while the number of turns (7) and spacing ($9.47 \\mathrm{e}-3$) are adjusted to balance impedance and axial ratio. The antenna achieves a low axial ratio (close to 1), ensuring the return loss is greater than $20 \\mathrm{~dB}$ between 2.3GHz to 2.4GHz with a strategically calculated gain of $9.03 \\mathrm{~dB}$ at the center frequency and sufficient bandwidth covering the GPS frequency band with VSWR close to 1, the antenna promises reliable signal reception. Impedance matching occurs from 2.4GHz. The helical antenna aligns with right-hand circular polarization, essential for GPS signals. The resulting radiation pattern exhibits a well-shaped coverage, characterized by high gain in the zenith direction and controlled gain in opposing directions. This design signifies a robust solution for GPS-based navigation, offering optimal performance across a range of key parameters.
Panoptic Segmentation using Mask2Former with Swin Transformers Cheluka Aneesha Patel, D Stitha Pragna, K Muni Narendra Babu, Munugala Akshay Kumar, K Swaraja, N Arun Vignesh 2024 4th International Conference on Intelligent Technologies Conit 2024, 2024 In today’s world, there is swift increase in the use of autonomous vehicles. There are different models that are proposed to understand the scene by segmenting and detecting the image into things(objects) and stuff(Background). Mask2Former a novel method for panoptic segmentation that incorporates Swin Transformers as its backbone is the model that is built In the proposed work for better scene understanding. This innovative architecture makes use of the hierarchical representation features of Swin Transformers, a cutting-edge transformer model well-known for its efficiency in handling massive image processing. As a result, it can function as the general-purpose foundation for image classification. The combination of Mask2Former and Swin Transformers provides a powerful approach to difficult segmentation problems, providing excellent accuracy and efficiency inside a single framework. This model significantly beats the best specialized architectures on three widely used datasets the Cityscapes, KITTI and the Coco. Mask2former with swin transformer achieves 64.2percent PQ on coco dataset.
Semantic Segmentation Using U-Net for Autonomous Driving Venkat Sai Natte, Jahnavi Kadicherla, Sri Divya Katukojwala, K Swaraja, N. Arun Vignesh, Srilakshmi Aouthu 3rd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics Icdcece 2024, 2024 Safe autonomous driving crucially depends on effective detection of nearby objects for hazard-free navigation. Semantic segmentation aids autonomous systems by enabling accurate environmental perception. However, identifying moving vehicles in images, especially when obscured, poses challenges. To address this, deep convolutional neural networks (CNNs), including UNET, are employed. By integrating CNNs' information across different scales into images of varying resolutions, the method enhances vehicle detection accuracy. Thorough training on real-world data refines the model, demonstrating quick and precise vehicle identification. Experimental results highlight significant improvements in detection accuracy (81.4%) and mean intersection over union (76.84%). This approach not only advances real-time vehicle detection but also emphasizes UNET's adaptability in dynamic traffic environments. The findings suggest a robust pathway for deploying dependable detection systems, enhancing overall autonomous driving safety.
Design of Dual Band Body Area Network Antenna Using CST Randhi Harika, Manda Arun Raj, Saraswatula Karthikeya Anirudh, N. Arun Vignesh, C. Gokul Prasad 2023 International Conference on Computer Communication and Informatics Iccci 2023, 2023
Vedic Multiplier for High-Speed Applications J. V. R. Sudhamsu Preetham, Perli Nethra, D. Chandrasekhar, Mathangi Akhila, N. Arun Vignesh, Asisa Kumar Panigrahy Lecture Notes in Networks and Systems, 2023
Soft Computing Approach To Prevent Derailments Due To Landslides S. Balambigai, P. V. Shreeram, J. Sureshkanna, S. Sasikala, S. Sowmika, N. Arun Vignesh 2023 14th International Conference on Computing Communication and Networking Technologies Icccnt 2023, 2023
Virtual Image Processing for Robot Automation C. Gokul Prasad, M Shobana, N Arun Vignesh, N. Kumareshan, E Konguvel, S. Madhusudhanan 2022 International Conference on Computer Communication and Informatics Iccci 2022, 2022
Deep Learning based Medical Image Classification A.Sahaya Anselin Nisha, Vamsidhar Enireddy, T Bernatin, Karthikeyan. C, D.Vijendra Babu, N.Arun Vignesh Proceedings 4th International Conference on Smart Systems and Inventive Technology Icssit 2022, 2022
A Study On Wideband Spectrum Monitoring Using NI USRP Laxmi Gouri Naga Sai Pratyusha, Kammela Keerthi, Kora Sathvika Reddy, Erukala Sai Sushma, N Arun Vignesh, V. Ayyem Pillai, N. Kumareshan 2022 International Conference on Computer Communication and Informatics Iccci 2022, 2022
Cross Coupled Power Effective Quick Level Shifter N. Sai Kiran, N. Arun Vignesh, S. Kanithan, E. Shobhana, N. Kumareshan, S. Madhusudhanan, Balambigai Subramanian, Prajith Prakash Nair 2022 International Conference on Computer Communication and Informatics Iccci 2022, 2022
Implementation of xor and edge identification method in steganography Dept. of E.C.E, Gokaraju Rangaraju Institute of Engineering, Technology, Hyderabad., Permella Abishai Jasper, D. Jayanthi, Dept. of E.C.E, Gokaraju Rangaraju Institute of Engineering, Technology, Hyderabad, N. Arun Vignesh, Dept. of E.C.E, Gokaraju Rangaraju Institute of Engineering, Technology, Hyderabad International Journal of Engineering and Advanced Technology, 2019
Implementation of low density parity check system using probabilistic gradient descent bit flipping decoder Gokaraju Rangaraju Institute of Engineering, Technology, Hyderabad, India., Venkateswara Rao Varri, N. Arun Vignesh, Gokaraju Rangaraju Institute of Engineering, Technology, Hyderabad, India., Asisa Kumar Panigrahy, Gokaraju Rangaraju Institute of Engineering, Technology, Hyderabad , India., C H Usha Kumari, Gokaraju Rangaraju Institute of Engineering, et al. International Journal of Innovative Technology and Exploring Engineering, 2019
Fungal disease in cotton leaf detection and classification using neural networks and support vector machine Professor in Department of ECE, GRIET, Hyderabad, Telangana, India., Ch. Usha Kumari, N. Arun Vignesh, Associate Professor in Department of ECE, GRIET, Hyderabad, Telangana, India., Asisa Kumar Panigrahy, Associate Professor in Department of ECE, GRIET, Hyderabad, Telangana, India., L. Ramya, lecturer in Department of ECE VNRVJIET, Hyderabad Hyderabad, Telangana, India., T. Padma, Professor in Department of ECE, GRIET, Hyderabad, Telangana, India. International Journal of Innovative Technology and Exploring Engineering, 2019
A Survey on Energy Efficient Image Transmission in WSN S. Kanithan, N. Arun Vignesh, Asisa Kumar Panigrahy, V Ayyem Pillai, E Karthikeyan, C.H. Usha Kumari, Sudharsan Jayabalan, T. Santosh Kumar 2019 2nd International Conference on Intelligent Computing Instrumentation and Control Technologies Icicict 2019, 2019
Improving the performance of quality of service parameters using mobile node positioning algorithm in WLAN Journal of Advanced Research in Dynamical and Control Systems, 2018
A cluster-based network architecture scheme for QoS improvement in WLAN International Journal of Networking and Virtual Organisations, 2017
