Mud architecture has played a crucial role in shaping human settlements in arid regions, offering sustainable and durable solutions for centuries. This study explores the historical evolution of mud architecture, highlighting its adaptability to extreme climatic conditions and its significance in preserving cultural heritage. The paper examines tra...

By Abdurahim Mannonov, Khurshid Samatov, Nilufar Fayzieva, Valisher Sapayev, Dadaxon Abdullayev, Nargiza Ruzmetova, Khafiza Khasanova

In the current era of data-intensive applications, including OTT services, IoT, and autonomous systems, efficient image compression is indispensable in order to minimize bandwidth consumption while preserving visual quality. Conventional compression techniques frequently fail to satisfactorily balance compression ratios and the preservation of crit...

By K. Subba Reddy, R. Arshiya

As incidents of gendered violence and child abuse increase, there is a need for intelligent, real-time safety systems that autonomously detect distress and initiate emergency action without user activation. Q-SAFE (Quantum AI for Real-Time Women & Child Safety) is an open-source, multi-modal mobile app, utilizing quantum-enhanced machine learni...

By N. Geetha, K. Janani, P. Mathushri, S. Harini, D. Vasantha Mallika

Preserving and interpreting historical engineering documents aids in appreciating the nature of scientific reasoning as well as technological advances. Digitization and detailed analysis are highly challenging for many of such documents which are handwritten, eroded and in delicate conditions. This paper presents research on reconstruction of histo...

By Navbakhor Iskandarova, Nargiza Burieva, Abdurahim Mannonov, Adil Kariev, Nodir Karimov, Zumrad Kasimova, Margubakhan Eshnazarova, Sadokat Abidova

Within the database infrastructures of large-scale enterprises and government organizations, preserving swift and dependable disaster recovery processes continues to be particularly challenging with increasing data volumes and greater complexity in systems. This study conducts an evaluative analysis of advanced failover and backup methods, comparin...

By Harsha Vardhan Reddy Kavuluri

The detection of stroke is vital since any delay in diagnosis may lead to significant disability or the loss of life. The existing predictive models fail to capture stroke symptoms with accuracy because of low complexity, and the ability to be used in the real-time situation in the clinical setting. In the following paper, an AI-based system of ear...

By D. Ushasree, A.V. Praveen Krishna, Ch. Mallikarjuna Rao, D.V. Lalita Parameswari

Predictive maintenance has become an important factor in improving the reliability and efficiency of industrial robots in the evolving environment of smart manufacturing. The proposed paper is a predictive maintenance framework based on AI to be implemented to multi-sensor industrial robots that will be used in a smart manufacturing setting. The po...

By Priya Vij, Ashu Nayak

The world aerospace industry is now facing an important shift from traditional metallic structures to high-tech advanced composite materials in order to meet the two-fold needs of structural optimization and environmental sustainability. This study examines the evolution of high-performance composite materials, particularly carbon fiber reinforced ...

By Ravinder Sharma, Shyam Maurya

Purpose- The main objective of the proposed paper is to create and implement a real-time wearable health monitoring system based on IoT, i.e., Oxy Sense-Wear, that will enable the constant control of the main physiological parameters, such as ECG, EMG, SpO2, body temperature, and physical activity. The system is aimed at long-term surveillance of t...

By M.N. Vimal Kumar, M. Pravin Kumar, Baskar Duraisamy, A.K. Jaithunbi, P. Samson Peter, V.M. Thejashri

Hazardous air pollutants (HAPs) can be a critical risk to the sustainability of the environment and human health, which must be addressed by highly sophisticated predictive models to eliminate risks successfully. In this study, the researcher presents a hybrid deep learning model that combines Convolutional Neural Networks (CNNs) with the ability t...

By K. Muralisankar, G. Balaji, C. Ramkumar, M. Vasuki, S. Vijayananthan, D. Angayarkanni, Mohammed Aslam, M. Narmatha