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Daily Archives: August 11, 2026

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Geosynthetic Reinforcement of Clay Subgrades in Flexible Pavements: A Review

Authors: Ramanuj Singh, Assistant Professor Hariram Sahu

Abstract: Flexible pavements founded on clay subgrades are prone to premature distress because clay soils frequently combine low bearing capacity with pronounced moisture sensitivity. Expansive clays undergo cyclic swelling and shrinkage that produce heave and cracking, while non-expansive clays exhibit low shear strength and high compressibility that lead to rutting and shear failure. Conventional remedies, such as soil replacement, chemical stabilization, and cohesive non-swelling cushions, are often costly, site-sensitive, or only partially effective, and the empirical California Bearing Ratio (CBR) design framework used across India does not explicitly capture swelling behaviour or the beneficial contribution of reinforcement. This paper presents a detailed literature review of the growing body of laboratory, test-track, and field research on the use of geotextiles and geogrids to reinforce clay subgrades beneath flexible pavements. The mechanisms of tensioned-membrane action in geotextiles and lateral-restraint/reinforced-mattress action in geogrids are examined, together with reported improvements in bearing capacity, rutting resistance, and pavement service life. Findings from Indian and international studies that employ the CBR test as the principal evaluation framework are synthesized, and Indian standards and codes relevant to reinforced-pavement design are discussed. The review identifies a persistent gap between the extensive experimental evidence for the benefits of geosynthetic reinforcement and the absence of a unified, quantitative, bearing-capacity-based design procedure that differentiates between expansive and non-expansive clay subgrade conditions, and concludes with directions for future research in this area.

DOI: https://doi.org/10.5281/zenodo.21885256

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Adaptive AI-Assisted Doppler Compensation and Predictive Handover Optimization for LEO Satellite Communication in 6G Non-Terrestrial Networks

Authors: Prateek Anand, Assistant Professor Rishi Sharma, Assistant Professor Gaurav Morghare

Abstract: Low Earth Orbit (LEO) satellite communication has emerged as a key enabler of sixth-generation (6G) Non-Terrestrial Networks (NTNs), offering global coverage, low propagation delay, and high-capacity broadband connectivity. However, the high orbital velocity of LEO satellites introduces significant challenges, including severe Doppler frequency shifts, rapidly varying channel conditions, and frequent handovers, which adversely affect communication reliability, throughput, and Quality of Service (QoS). Existing Doppler compensation and handover mechanisms are generally treated as independent processes and often rely on static threshold-based strategies or computationally intensive artificial intelligence (AI) models, limiting their adaptability in highly dynamic satellite communication environments. This paper proposes an Adaptive AI-Assisted Doppler Compensation and Predictive Handover Optimization (AIDCPHO) framework for LEO satellite communication in 6G Non-Terrestrial Networks. The proposed framework integrates real-time Doppler estimation, AI-assisted predictive handover decision-making, adaptive beam selection, and dynamic link quality assessment into a unified optimization model. A predictive mobility module estimates future satellite-user link conditions using orbital dynamics and user mobility information, while an adaptive Doppler compensation module minimizes frequency estimation errors before communication degradation occurs. Furthermore, a multi-parameter handover decision algorithm utilizes Signal-to-Noise Ratio (SNR), Doppler shift, elevation angle, received signal strength, and predicted link quality to proactively initiate seamless handovers, thereby reducing service interruption and packet loss. The proposed framework is implemented and evaluated using MATLAB-based simulations that model realistic LEO satellite orbital movement, time-varying communication channels, and user mobility scenarios.

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An IoT-Enabled Multi-Sensor Autonomous Rescue Robot for Earthquake Search and Rescue Operations

Authors: Assistant Professor Biju George.G

Abstract: Earthquakes often create hazardous environments that delay rescue operations and increase risks to emergency responders. This paper presents a low-cost Internet of Things (IoT)-enabled autonomous rescue robot designed to assist in earthquake search and rescue missions through real-time monitoring and multi-sensor integration. The proposed system employs an Arduino Uno as the central controller and integrates a Passive Infrared (PIR) sensor for human detection, an ultrasonic sensor for obstacle avoidance, an MQ-series gas sensor for hazardous gas detection, a GPS module for victim localization, and an ESP32-CAM module for live video surveillance. Sensor data are transmitted through an ESP8266 NodeMCU to the Blynk IoT platform, enabling remote monitoring of environmental conditions, survivor alerts, and robot location. The developed prototype was experimentally evaluated under laboratory conditions to validate its sensing, navigation, communication, and monitoring capabilities. Experimental results demonstrate reliable human detection, obstacle avoidance, hazardous gas monitoring, GPS-based localization, and real-time data transmission with low implementation cost and reduced computational complexity. The proposed system offers a practical and scalable solution for improving rescue efficiency while minimizing the exposure of rescue personnel to hazardous environments. The modular architecture also provides flexibility for future enhancements using artificial intelligence and advanced sensing technologies.

DOI: https://doi.org/10.5281/zenodo.21884018

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