International Journal of Academic and Industrial Research Innovations(IJAIRI)

Abstract: This study investigates a hybrid Quantum-AI framework for real-time cybersecurity threat detection and adaptive defense in high-velocity network environments. The central research problem concerns the increasing mismatch between dynamic cyberattacks and conventional intrusion-detection pipelines that are accurate under benchmark conditions but insufficiently reliable under latency, drif…

Abstract This study investigates ultra-low-power edge intelligence as a co-design problem spanning learning algorithms, compilation/runtime systems, and hardware microarchitecture. The central claim is that energy-efficient edge AI emerges from joint optimization of (i) model structure and numerical precision, (ii) data movement across memory hierarchies, and (iii) accelerator-aware execution tha…

This study investigates satellite-based measurement, reporting, and verification (MRV) as a credibility backbone for carbon removal and durable climate claims. The central premise is that high-integrity carbon removal requires not only process monitoring at projects (e.g., direct air capture, enhanced weathering, afforestation) but also independent, physics-based evidence that atmospheric greenho…

Abstract: This study investigates contagion between cryptocurrencies and traditional assets through the joint lenses of volatility clustering and tail-risk spillovers. The proposed empirical framework treats contagion as a two-layer phenomenon: (i) volatility persistence and cross-market volatility transmission that amplify risk during turbulent periods, and (ii) tail-event dependence in which ex…

Abstract: This study investigates explainable artificial intelligence (XAI) models for predicting 30-day adverse events and enabling quality improvement across public and private health service systems. The framework integrates clinical records (case-mix, comorbidity, vital signs, laboratory markers, and process indicators) with patient-generated sensor summaries (activity, sleep, and heart-rate …

Abstract: This study investigates quantum-safe modernization strategies for critical infrastructure by proposing a rigorous post-quantum (PQ) migration and verification framework that treats cryptographic transition as a safety-critical, multi-system engineering program rather than a routine software upgrade. The core argument is that infrastructure operators face two coupled risks: (i) cryptanal…

Abstract: This study investigates evolution-resistant anti-biotic strategies by integrating AI-assisted drug discovery with adaptive treatment protocols designed to suppress or redirect resistance evolution. The foundational premise is that antimicrobial resistance (AMR) is simultaneously a molecular design problem—requiring new chemotypes and targets—and a dynamical control problem—requiring dos…

Abstract: This study investigates self-healing smart infrastructure as a materials–systems paradigm in which structural components incorporate programmable repair chemistries and embedded sensing to autonomously detect, localize, and mitigate damage. The central premise is that lifetime extension of bridges, pavements, pipelines, and coastal assets is increasingly limited by distributed microcrac…

Abstract: This study investigates a closed-loop neuroprosthetic framework that couples real-time intention decoding with bidirectional sensory feedback, targeting dexterous upper-limb control under clinically realistic constraints of latency, stability, and interpretability. The proposed framework formalizes intention decoding as a continuous regression problem and integrates an explicit feedback…

Abstract: This study investigates how disaster digital twins can be operationalized as AI world models to anticipate cascading infrastructure failures under compound hazards. The central premise is that critical services—power, water, telecommunications, healthcare, and transportation—form a tightly coupled, multi-layer network in which disruptions propagate nonlinearly through physical dependenc…

Abstract: This study investigates programmable carbon capture as a synthetic-biology-enabled pathway for accelerating and scaling CO₂ mineralization into stable carbonate solids. The central hypothesis is that durable carbon removal can be engineered as a controllable biocatalytic process by coupling (i) genetically programmable CO₂ hydration and alkalinization modules, (ii) controllable nucleati…

Abstract: This study investigates quantum-enhanced artificial intelligence (QEAI) models for climate-resilient crop production and sustainability-oriented decision support in agriculture. The framework integrates agroclimatic signals (rainfall, temperature, evapotranspiration, heatwave and dry-spell indicators, and vapor-pressure deficit) with sensor-derived crop-state variables (soil moisture, c…

Abstract: This study investigates hybrid Quantum–AI optimization models for improving energy efficiency and production yield in industrial manufacturing systems under realistic sensor-data constraints. The proposed framework couples (i) a physics-consistent energy model for electro-mechanical drives and process stages with (ii) an AI layer for state estimation and yield-risk scoring, and (iii) a …

Abstract: This study investigates how AI-driven trade analytics can be integrated with econometric identification to evaluate Free Trade Agreement (FTA) outcomes and to quantify changes in industrial competitiveness using trade microdata. The empirical design is structured around a policy evaluation workflow that combines (i) event-study and difference-in-differences estimators for causal attribu…

Abstract: This study investigates systemic post-quantum cyber risk as a governance and coordination problem in critical infrastructure, where cryptographic transitions interact with interdependent attack surfaces, heterogeneous operator costs, and policy constraints. A mechanism-design perspective is developed to formalize incentive-compatible adoption of crypto-agile controls under network exter…

Abstract: This study investigates cascade resilience during the post-quantum transition across coupled finance, telecommunications, and industrial control systems (ICS), using marine robotics with edge autonomy as the operational anchor. Migration failures can disable services even when links exist, because suite negotiation, certificates, or key management become incompatible across stakeholders…

Abstract: This study investigates quantum-accelerated intelligence as a national capability that integrates hybrid artificial intelligence with quantum and quantum-inspired optimisation. In many public infrastructures, predictive models deliver situational awareness, but operational value is constrained by hard, time-critical optimisation tasks such as scheduling, routing, and resource allocation…

Chronic diseases represent a significant burden on global healthcare systems due to their long-term nature and high treatment costs. Early diagnosis is critical in managing these diseases effectively. This research proposes the development and evaluation of AI-powered predictive models leveraging electronic health record (EHR) data to enable early detection of chronic conditions such as diabetes,…

Abstract: As artificial intelligence (AI) increasingly informs decisions in critical sectors such as healthcare, finance, and governance, concerns regarding algorithmic opacity and fairness have intensified. This research investigates the integration of Human-in-the-Loop (HITL) mechanisms as a strategy to enhance transparency, interpretability, and accountability in AI systems. Using real-world d…

Abstract: The widespread deployment of black-box artificial intelligence (AI) systems in high-stakes domains such as healthcare, finance, and criminal justice has intensified the demand for transparent and accountable decision-making. This study investigates the utility of counterfactual explanations as a method for auditing opaque AI models. By answering the question of what minimal change in in…