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Chapters
12
Language
English
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Published
July 27, 2025
This book is a comprehensive guide for software developers and engineers seeking to build advanced browser-based 3D applications, specifically focusing on creating an interactive virtual design lab for mobile phone hardware and the Android OS. Titled 'Sloinexta - Mobile Phone Lab,' by Vikram Singh Sankhala, this 12-chapter work delves into the practical application of React and Three.js to visualize intricate mobile phone components, from processors and displays to sensors and batteries, through interactive 3D models with exploded views. It further illuminates the complexities of Android OS architecture by visualizing its system layers, enabling a deeper understanding of hardware-software interaction. The core motivation behind 'Sloinexta - Mobile Phone Lab' is to address the increasing complexity of modern mobile devices and the demand for accessible, interactive educational tools. The book provides step-by-step walkthroughs of the end-to-end design and production process, including prototyping, testing, and manufacturing, supported by interactive timelines and production pipeline visualizations. It empowers readers to foster innovation and collaboration through features like simulation testing, virtual reality exploration, real-time cost calculation, and supply chain optimization recommendations, ultimately bridging the gap between theoretical knowledge and practical application in mobile technology development.
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Start Writing NowVikram Singh Sankhala offers a unique analytical perspective on Vedic astrology, leveraging his expertise in multi-modal AI, agentic systems, and data-driven solutions to decode ancient principles through modern scientific frameworks. Sankhala's innovative approach bridges traditional wisdom with contemporary visualization techniques, making complex astrological concepts accessible. His mission is to unlock timeless insights using today's analytical tools, viewing Vedic astrology as humanity's oldest data science.
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Solinexta Cloud Master: Deploying Websites and ML Models with Kubernetes and Streaming Pipelines
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