Daily Archives: July 9, 2026

Authors: Swaminathan Mani

Abstract: This paper introduces the Universal Substrate (US), a dis-crete, non-local information-processing architecture that serves as the ontological basis for the phys-ical universe. This model proposes that the observable cosmos is an Emergent User Interface (UI), where the laws of physics are not fundamental constants but identified as algorithmic protocols optimized for systemic stability. By reinterpreting spacetime as a Topological Information-Braiding manifold, this model provides a unified resolution – reconciling the discrete nature of Quantum Mechanics with the geometric curvature of General Relativity through a single, self-correcting Au-todidactic Meta-Algorithm.

Published by: vikaspatanker

Authors: Jasjit Singh Samagh, Tushar Sharma, Sumit Kharra

Abstract: AI and wearable sensors are revolutionizing the modern workout routine, offering real-time health tracking, tailored exercise plans, and intelligent performance optimization. The present research provides an extensive survey of AI-driven smart fitness systems with focus on upcoming machine learning and deep learning techniques that could be incorporated with wearable gadgets for instant wellness measurement and guidance. It explores cutting-edge techniques such as Convolutional Neural Network, Recurrent Neural Network, Spatio-temporal Graph Convolutional Network, Transformer-based model, and Virtual Fitness Assistants powered by Large Language Model, and delves into the applications of these models for posture correction, activity recognition, adaptive training, physiological recovery analysis, injury-risk prediction, and personalized wellness management. The paper also explores major technical hurdles like multimodal sensor data fusion, computational efficiency on the edge, privacy-preserving federated learning, explainable AI, and long-term personalization. Finally, new research trends such as digital twins, generative AI, and intelligent coaching with context are discussed to pave the way to the future of AI-powered fitness ecosystems. This research offers a technical foundation and insights to computer science researchers, practitioners and students on next generation intelligent fitness systems.

Published by: vikaspatanker

Authors: Swaminathan Mani

Abstract: Generative Artificial Intelligence has changed the way we make images from text. Now we can make quality images from what we write. This is because of models that use special architectures. These models are really good at making images that look real. Are about the right thing. We can use these models to make art, design and ads. They are also useful in education, healthcare and gaming. This saves us time and money because we do not have to make images by hand. This paper is about how we can make images from text using Generative Artificial Intelligence. We look at how the models work and what's new about them. We talk about models like Stable Diffusion, DALL·E and Imagen. We look at how the whole process works, from getting the text ready to making the image. We also think about how to make the images better by using the words. We discuss what is good and bad about the models we have now. We also look at what other people have found out about making images from text. We compare the ways to do it and talk about what is new and interesting. We think about how we can make images that're just what we want and how we can make the models work better and faster. Generative Artificial Intelligence models that use diffusion are good at making images that look real. Are about the right thing. They open up possibilities, for art and industry. This paper ends by talking about what we need to do to make the models better and more responsible.

DOI: https://doi.org/10.5281/zenodo.21248944

Published by: vikaspatanker

Authors: Teju M , Assistant Professor Divakar K M

Abstract: Generative Artificial Intelligence has changed the way we make images from text. Now we can make quality images from what we write. This is because of models that use special architectures. These models are really good at making images that look real. Are about the right thing. We can use these models to make art, design and ads. They are also useful in education, healthcare and gaming. This saves us time and money because we do not have to make images by hand. This paper is about how we can make images from text using Generative Artificial Intelligence. We look at how the models work and what's new about them. We talk about models like Stable Diffusion, DALL·E and Imagen. We look at how the whole process works, from getting the text ready to making the image. We also think about how to make the images better by using the words. We discuss what is good and bad about the models we have now. We also look at what other people have found out about making images from text. We compare the ways to do it and talk about what is new and interesting. We think about how we can make images that're just what we want and how we can make the models work better and faster. Generative Artificial Intelligence models that use diffusion are good at making images that look real. Are about the right thing. They open up possibilities, for art and industry. This paper ends by talking about what we need to do to make the models better and more responsible.

DOI: https://doi.org/10.5281/zenodo.21274709

Published by: vikaspatanker

Authors: Dhanashree Sanjay Kale, Guidance of Ar. Dilip Jade, Ar. Radhika Raut

Abstract: Traditional architectural typologies for neuro-trauma rehabilitation heavily rely on institutionalized, clinical frameworks. While satisfying baseline medical and physical accessibility codes, these spaces often inadvertently induce spatial alienation, reinforcing a patient's perceived systemic limitations. This research paper investigates the intersection of environmental psychology and neuro-architecture to propose an alternative paradigm: an integrated rehabilitation and para-sports training facility structured around a "Gradient of Autonomy." Utilizing a qualitative and comparative spatial analysis methodology, this study examines how progressive spatial thresholds, sensory calibration, and intentional sightlines accelerate the psychological transition from a passive patient to an empowered, elite para-athlete. The findings demonstrate that replacing sterile, clinical aesthetics with calibrated acoustic zoning, circadian lighting systems, and dignified tactile wayfinding significantly mitigates sensory overload while fostering spatial agency. The paper concludes by presenting a programmatic matrix and architectural guidelines for future universally empowering athletic environments.

DOI: https://doi.org/10.5281/zenodo.21274067

Published by: vikaspatanker

Authors: Akshay Surendra Pimple, guidance of Ar. Anand A. Pande

Abstract: Temporary urbanism plays a critical role in managing dynamic human movement, particularly during large-scale mass gatherings, pilgrimages like the Kumbh Mela, and disaster-relief scenarios. While these transient settlements must rapidly provide vital infrastructure, safety, and shelter for millions of people, traditional construction methods relying on bamboo, corrugated metal sheets, and plastic coverings face severe limitations in durability, environmental impact, comfort, and reusability. This research investigates the untapped potential of innovative alternative materials and modular construction techniques as environmentally responsive solutions to replace conventional, inefficient practices. Through rigorous experimentation and design exploration, this study aims to develop safer, highly adaptable, and affordable temporary architectural systems that ensure rapid assembly and structural utility while minimizing ecological footprints. Furthermore, the paper analyzes the socio-economic scope of these systems, highlighting future opportunities for local skill development, manufacturing employment, and sustainable material lifecycles. Ultimately, this research offers a progressive framework for temporary architecture that balances immediate human comfort with long-term sustainable growth.

DOI: https://doi.org/10.5281/zenodo.21273750

Published by: vikaspatanker