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816 articles for “framework integration”
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Smart Contract: A New Buzz Word for Reliable Decentralized Network
Abstract: Blockchain technology has emerged as a foundational distributed-ledger architecture enabling decentralized, transparent, and tamper-resistant data management across diverse digital ecosystems. This paper presents an integrated review of blockchain fundamentals, consensus mechanisms, smart contract design, and real-world applications beyond cryptocurrencies. It discusses the evolution of smart contracts as automated, self-executing programs that remove intermediaries and ensure deterministic execution, while highlighting critical security vulnerabilities such as reentrancy, arithmetic overflows, and improper access …
Published in Journal of Open Source Developments · Vol. 13, Issue 1, 2026 · pp. 35–41 Read article
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Demand Side Load Management Using Intelligent Metering/Billing System
Abstract: Regular power framework is progressing from the integrated supply side administration to the decentralized supply and demand-side administration, because of the continuous power sources in the reconstruction of intensive structures and era (DG) and Smart Grids (SG) or smart distribution system (SDS) With the past two decades. Accordingly load the board under the new working condition turns out to be more troublesome than that under the customary condition. This paper …
Published in Journal of Advances in Shell Programming · Vol. 6, Issue 2, 2019 · pp. 17–21 Read article
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Efficient Energy Management using Artificial Intelligence (AI) and Machine Learning (ML) in Chemical Industry
Abstract: The globe is moving toward higher usage of renewable energy sources, particularly solar and wind energy, as a result of depleting fossil fuel supplies and growing environmental concerns. There are several forecasting methods available for effective wind energy utilization. This review uses algorithms for predicting solar and wind energy as well as artificial intelligence (AI) techniques. A wind-coal coupling energy system planning scheme was designed to lower the high energy …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 2, 2025 · pp. 33–50 Read article
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A Systematic Study of AI-Powered Robotics for Ocean Cleanup of Plastics
Abstract: The escalating crisis of plastic pollution in marine ecosystems demands innovative solutions beyond conventional cleanup methods. This paper presents a systematic study of artificial intelligence (AI)-powered robotics for ocean plastic cleanup, evaluating their efficiency, technological advancements, and challenges. Autonomous systems, such as AI-driven surface drones (ASVs), underwater robots (autonomous underwater vehicles/remotely operated vehicles [AUVs/ROVs]), and swarm robotics, leverage machine learning (ML) and computer vision to detect, classify, and collect plastic …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 1–10 Read article
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Enhancing MRO Documentation Through Automated Translation of Non-Standard English to Simplified Technical English Using Offline LLMS
Abstract: Maintenance, Repair, and Overhaul (MRO) operations rely heavily on accurate and consistent documentation to ensure operational safety and compliance. However, the presence of non-standard English in technical documents often leads to ambiguity, misinterpretation, and inefficiencies in maintenance processes. This study presents an innovative solution that leverages an offline Large Language Model (LLM) to automatically translate non-standard English in MRO documents into standardized and technically precise language. By integrating predefined linguistic …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 9–15 Read article
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Impacts of Climate Change and Anthropogenic Stressors on Marine Ecosystems: A Comparative Study of Coral Reefs, Kelp Forests, and Arctic Fjords
Abstract: The accelerating impacts of climate change and human activities are profoundly reshaping marine ecosystems, threatening biodiversity, and altering trophic dynamics. This study synthesizes recent research on the responses of marine flora and fauna to temperature fluctuations, ocean acidification, pollution, and overfishing, highlighting the cascading effects on primary production, nutrient cycling, and ecosystem resilience. Using a combination of field surveys, remote sensing data, and meta-analytical approaches, we quantified biodiversity shifts across …
Published in International Journal of Marine Life · Vol. 3, Issue 1, 2026 · pp. 17–24 Read article
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Genomic Characterization of Emerging Arboviruses in Rural India
Abstract: Arboviruses (arthropod-borne viruses) represent a rapidly evolving group of pathogens responsible for significant morbidity and mortality, particularly in tropical and subtropical regions. Rural India, characterized by dense vector populations, changing ecological patterns, and limited healthcare infrastructure, has become a hotspot for the emergence and re-emergence of arboviral diseases such as dengue, chikungunya, Japanese encephalitis, and more recently, Zika virus infections. Advances in genomic technologies, including next-generation sequencing (NGS), metagenomics, and …
Published in International Journal of Pathogens · Vol. 3, Issue 2, 2026 · pp. 1–8 Read article
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Atypical Psychiatric Presentations of Autoimmune Encephalitis: A Case Series and Proposed Clinical Approach to Diagnosis
Abstract: Background: knowledge and detection of seronegative autoimmune encephalitis (AE) is growing rapidly, but typical psychiatric presentations risk misdiagnosis or delay in diagnosis with worse prognostic outcomes. Paraclinical markers are useful when positive, and integral to the current diagnostic framework yet have limited sensitivities leaving an unknown percentage of patients without diagnosis or treatment. Cases not meeting diagnostic criteria pose a particular clinical challenge regarding diagnosis and treatment decision making and …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 12, Issue 2, 2022 · pp. 26–37 Read article
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Enhancing Explainability in Machine Learning Based Spam Email Detection Using LIME and SHAP
Abstract: Spam emails represent a continual and irritating cybersecurity issue due to the fast expansion of cyberspace communication. These messages are unwanted and, in some cases, dangerous, such as phishing schemes, identity theft, and the propagation of malware. They cause severe financial and data security threats to individuals and organizations. Conventional spam detection techniques, such as rule-based spamming, blacklisting, and keyword classification, are techniques that find it difficult to match adaptive …
Published in Journal Of Network security · Vol. 14, Issue 2, 2026 · pp. 35–48 Read article
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Mouse-less Interaction Using Augmented Reality
Abstract: This project aims to revolutionize computer interaction in augmented reality environments by developing a mouse-less system operated by fingers in the air. The conventional use of physical mouse restricts user movement and immersion in virtual environments. The project's primary objectives revolve around tackling issues related to precision, response time, the identification of gestures, and the seamless integration of augmented reality. The proposed solution involves selecting appropriate motion tracking technologies and …
Published in Journal of Operating Systems Development & Trends · Vol. 10, Issue 2, 2023 · pp. 24–35 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 · pp. 15–24 Read article
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Multilingual Education and Language Policy in a Globalized World: Toward Inclusive and Equitable Learning Systems
Abstract: Multilingual education involves teaching and learning in two or more languages, promoting linguistic diversity and enhancing educational outcomes. It acknowledges learners’ native languages and integrates them with dominant or global languages to foster inclusivity and cognitive development. Multilingual education (MLE) serves as a critical framework for promoting inclusivity and equity within increasingly globalized and culturally diverse classrooms. This paper explores the role of MLE and the influence of language policies …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 64–74 Read article
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A Study On Hybrid Renewable Energy System
Abstract: The market of sun oriented warm and photovoltaic power age is developing quickly. Novel thoughts on half and half sun oriented innovation develop for a wide scope of uses, for example, in structures, handling plants, and horticulture. In the structure area specifically, the restricted structure space for the convenience of sunlight based gadgets has driven an interest on the utilization of cross breed sun based innovation for the multi age …
Published in Journal of Microelectronics and Solid State Devices · Vol. 8, Issue 2, 2021 · pp. 33–37 Read article
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Circadian Regulation of Lipid Peroxidation in the Brain: Linking Ferroptosis to Neurodegenerative Vulnerability
Abstract: The human brain operates through highly coordinated physiological and biochemical processes that regulate cognition, behavior, and neural adaptability. Central to these processes are mechanisms governing brain function, neurophysiology, and neuroplasticity, which are increasingly recognized to be influenced by circadian rhythms. Recent advances in cognitive neuroscience, neuroimaging, and behavioral neuroscience have revealed that disruptions in circadian regulation can significantly impact oxidative balance within the brain, particularly through enhanced lipid peroxidation. Lipid …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 1–14 Read article
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Revitalizing São Cristóvão: Integrating Industry, Commerce, and Community for a Sustainable Urban Future
Abstract: This paper introduces a comprehensive framework for the sustainable regeneration of São Cristóvão, a historically industrial district in Rio de Janeiro, South America, which presently demonstrates significant urban deterioration, socio-economic instability, and increasing environmental hazards. Through an interdisciplinary methodology integrating spatial analysis, ethnographic profiling, environmental assessment, and stakeholder engagement, the study develops a phased master plan aimed at transforming the neighborhood into a resilient, inclusive, and economically diverse urban environment. …
Published in International Journal of Urban Design and Development · Vol. 4, Issue 1, 2026 · pp. 58–68 Read article
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Remote Sensing and Atmospheric Modelling: Data, Processes, Integration and Future Directions
Abstract: Atmospheric modelling plays a central role in weather forecasting, climate projection, and air quality assessment; however, the availability, accuracy, and representativeness of atmospheric observations fundamentally constrain its reliability. Over the past two decades, rapid advances in remote sensing (RS) have transformed atmospheric observation by providing spatially continuous, multiscale measurements of key atmospheric variables, including aerosols, trace gases, clouds, precipitation, and atmospheric thermodynamic profiles. This review synthesises recent progress in integrating …
Published in International Journal of Atmosphere · Vol. 3, Issue 1, 2026 · pp. 54–67 Read article
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A GIS and MCDA Framework for Land Suitability Analysis in Sustainable Agriculture
Abstract: This study examines land suitability for sustainable agriculture by integrating Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA) as tools to optimize agricultural planning. Sustainable agricultural practices are increasingly critical to meet global food demands without depleting essential land resources. This research focuses on assessing specific parameters that determine the agricultural viability of land, including soil characteristics, topography, climatic conditions, and water availability. These criteria are integral to understanding …
Published in International Journal of Land · Vol. 1, Issue 2, 2024 · pp. 30–34 Read article
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Predictive Analytics for Student Well-Being and Occupational Success
Abstract: The integration of predictive analytics into higher education has significantly transformed institutional decision-making processes. However, prevailing implementations remain predominantly performance-centered, focusing on dropout prediction and grade forecasting rather than holistic developmental outcomes. Concurrently, higher education systems worldwide are confronting escalating concerns regarding student mental health, disengagement, career uncertainty, and labor market volatility. These intersecting challenges necessitate a broader theoretical reconceptualization of predictive analytics—one that integrates psychological well-being and long-term occupational …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 155–163 Read article
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Application-Driven Rule-Based Framework for Lubrication Failure Modes in Industrial Systems
Abstract: Modern lubricants increasingly rely on polymer-based composites, integrating synthetic base oils, polymer thickeners and solid additives like MoS₂ and PTFE for high-performance applications. These formulations not only enhance thermal and mechanical stability but also enable low-friction operation across diverse industrial conditions. Lubrication-related failures represent a critical cause of unplanned downtime and reduced reliability in industrial machinery. This paper presents an application-driven, rule-based framework designed to assess and mitigate lubrication failure …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 522–531 Read article
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Multi-Parameter Biomedical Sensor-Based Mental State Classification Using EEG And Deep Learning Techniques
Abstract: With mental health concerns becoming increasingly widespread, there is a strong need for systems that can monitor conditions like stress, anxiety, and fatigue in a continuous and non- invasive manner. This research proposes a novel multi-parameter biomedical sensing framework for mental state classification by integrating electroencephalography (EEG) signals with physiological parameters, including body temperature acquired using LM35 sensors, heart rate from pulse sensors, and blood oxygen saturation (SpO₂) measurements. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 1–8 Read article