Daily Archives: September 23, 2025

Authors: Abdullah Tariq

Abstract: The evolution of iOS application development has witnessed a significant shift from traditional monolithic architectures to more sophisticated patterns that balance modularity with performance. This paper examines the concept of modular monoliths in large-scale iOS applications, exploring how this architectural pattern addresses the dual challenges of code reusability and runtime performance. Through analysis of implementation strategies, performance metrics, and real-world case studies, we demonstrate that modular monoliths offer a pragmatic middle ground between rigid monoliths and complex microservices architectures. Our findings suggest that when properly implemented, modular monoliths can achieve up to 40% better build times, 25% improved memory efficiency, and significantly enhanced developer productivity while maintaining the deployment simplicity of monolithic applications.

DOI: https://zenodo.org/records/17183546

Published by: vikaspatanker

Authors: Sangani Harshil, Kalariya Meet, Baraiya Ravi, Vasani Bhumil, Dr. Vikram B.Kaushik

Abstract: The ability to automatically describe visual content through natural language represents a compelling frontier in artificial intelligence research. Our work addresses this complex challenge by developing a sophisticated neural architecture that translates visual information into coherent textual descriptions. The methodology we employed centers on a two-stage approach: initially, we leverage the robust feature extraction capabilities of InceptionV3, a well-established convolutional neural network, to visual elements present in uploaded images. The extracted visual representations then feed into our custom language generation pipeline, built around a Gated Recurrent Unit (GRU) architec- ture. What distinguishes our implementation is the incorporation of a spatial attention module that enables selective focus across different image regions during the caption formation process. This attention-driven approach mirrors human visual processing, where we naturally emphasize certain areas while describing a scene. To validate the practical utility of our research, we constructed an intuitive web-based platform using Streamlit framework. This interactive system allows users to seamlessly up- load photographs and receive instantaneous caption generation, enhanced with audio narration capabilities through integrated speech synthesis technology.

Published by: vikaspatanker