Quaid-e-Awam University of Engineering, Science & Technology

Rapid urbanization combined with the intensification of extreme rainfall under climate change has substantially increased flood risk in coastal megacities, particularly in data-scarce regions. Conventional flood risk assessments predominantly rely on hydrometeorological and physical indicators, often neglecting real-time societal response and infrastructure stress. This study develops an integrated framework for flood risk prediction by coupling social media intelligence with urban morphology to capture both physical vulnerability and dynamic public response during extreme rainfall events. The framework is applied to Karachi, Pakistan, using the 2022 monsoon floods as a representative climate extreme. A dataset of 8,732 flood-related georeferenced social media posts was analyzed using natural language processing, sentiment analysis, topic modeling, and machine learning techniques. Public Concern Index and Public Sentiment Index metrics were employed to quantify temporal variations in public response, revealing that flood-related discussions peaked during extreme rainfall days, with Public Concern Index values reaching 17.28

The growing global demand for clean and reliable power has accelerated the transition from conventional fossil fuels to renewable energy sources. Among emerging solutions, floating renewable energy (FRE) systems have attracted significant attention for their ability to harness solar, wind, and hydropower resources on water surfaces while minimizing land-use conflicts. Despite rapid progress in individual technologies, a unified assessment covering their technical maturity, performance, and environmental impact remains limited. This study provides a comprehensive comparative review of the main FRE technologies floating photovoltaic (FPV), floating offshore wind turbines (FOWT), and floating hydropower, tidal, and wave energy systems. The analysis is based on a critical synthesis of recent research and industrial data, evaluating each technology in terms of efficiency, energy yield, levelized cost of energy (LCOE), technology readiness level (TRL), and operational challenges. The results show that FPV currently represents the most mature and cost-effective option, benefiting from high scalability and minimal environmental disturbance. FOWTs demonstrate strong potential for large-scale deployment but require further optimization in mooring stability and maintenance strategies. Marine-based systems such as tidal and wave energy remain at an early stage, constrained by technological and economic limitations. Overall, the findings highlight that hybrid FRE configurations combining solar, wind, and hydropower components offer the most promising pathway toward stable, high-efficiency, and sustainable offshore power generation. Continued research on advanced materials, system integration, and environmental resilience is essential to enhance the long-term viability of floating renewable systems in future energy transitions.

This study develops and empirically evaluates an Adaptive Gamification Design Model (AGDM) to address programming learning difficulties (PLDs). A three-phase mixed-methods design was employed. Phase I used a PRISMA-guided systematic review of studies published from 2010 to 2025 (N = 112) to construct a multidimensional Programming Learning Difficulty Taxonomy (PLDT) encompassing cognitive, affective, and instructional challenges. In Phase II, the taxonomy was validated through exploratory and confirmatory factor analyses of survey data from 842 undergraduate computer science and software engineering students at four public universities. Phase III comprised a 14-week quasi-experimental intervention involving a control group (n = 142) and an adaptive-gamification group (n = 144). Cognitive load, syntax anxiety, and self-efficacy deficit significantly predicted course failure. Compared with traditional instruction, the AGDM environment produced higher academic performance and intrinsic motivation and reduced the dropout rate from 34% to 12%. Structural equation modeling indicated that engagement and self-efficacy mediated the relationship between adaptive gamification and academic performance. The framework is operationalized through the Adaptive Gamification Optimization Algorithm (AGOA), which dynamically adjusts task difficulty, feedback scaffolding, and motivational incentives according to each learner's PLDT profile. The study contributes a validated taxonomy and a scalable adaptive-gamification framework that can be integrated into computing curricula to support competence, retention, and personalized learning.

The rapid penetration of distributed energy resources (DERs) is transforming consumers into prosumers, enabling decentralized peer-to-peer (P2P) energy markets. However, a major obstacle to their practical use is making sure that trades based on economics don’t break the physical limits of the distribution grid. This paper presents an innovative, entirely decentralized, and contextually aware Federated P2P (FP2P) market framework to tackle this issue. The framework co-optimizes the well-being of all prosumers with the safety of the grid by putting a linearized AC power flow model directly into a blockchain-based market clearing system. The main new thing about it is a proactive congestion management system that uses a Federated Learning (FL) architecture that protects privacy. It uses a Graph Neural Network (GNN) to predict the likelihood of line congestion. This predicted risk is turned into a dynamic grid fee, which keeps the market from going to unsafe operating points. The proposed FP2P framework was rigorously validated through a high-fidelity co-simulation on a modified IEEE 37-bus test feeder using real-world prosumer, weather, and market data. Results demonstrate that our approach successfully eliminates grid congestion events, significantly increases total prosumer profit, and reduces peak substation load compared to centralized, unmanaged P2P, and rule-based control baselines. The complete, AI-driven solution this work provides that bridges the gap between market economics and grid physics will enable future decentralized energy markets to function in a safe, efficient, and scalable way.

Floating renewable energy technologies have emerged as promising solutions to overcome land scarcity, access high-quality marine and inland energy resources, and support large-scale decarbonization. In recent years, significant advances have been reported in floating photovoltaic systems; however, a balanced and systematic assessment of floating solar, wind, and water-based renewable energy technologies remains limited. This review presents a comprehensive and technology-neutral analysis of floating photovoltaic, floating offshore wind, and floating water-based (wave and tidal) energy systems. For each technology, the review consistently examines operational principles, the current state of the art and existing floating solutions, key benefits and limitations, and emerging research trends and gaps. A unified comparative assessment is then conducted using common performance indicators, including technology readiness level, energy yield characteristics, economic viability, and system-level constraints. Finally, the review explores the potential integration of multiple floating renewable technologies, highlighting hybrid configurations and advanced concepts such as floating energy islands. By providing a coherent and balanced framework, this study supports informed decision-making and future research directions for the development and deployment of floating renewable energy systems.