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1977 articles for “intelligent scholastic frameworks” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Intelligent Cleaning Machine
Abstract: DC motors, Ultrasonic sensor, Vacuum cleaner and EZ-Bv4 controller are used to design the cleaning machine. When command is given to controller by using an android application, then we can control the direction of machine and can get the place clean by switching the vacuum cleaner button. In order to avoid obstacles ultrasonic sensors can be used.Cite this Article Mehfuza Holia, Nachiket Bhoi, Hardik Devganiya et al. Intelligent Cleaning Machine. …
Published in Current Trends in Information Technology · Vol. 8, Issue 3, 2018 · pp. 13–17 Read article
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Evaluation of Ensemble and Deep Learning Classifiers on CSE-CIC-IDS2018 Dataset for Intelligent NIDS
Abstract: Network Intrusion Detection System (NIDS) plays an active role in preventing cyberattacks by early detection of threats before it really starts affecting targeted information services. Over the years, many intrusion detection system (IDS) have been developed applying signature or rule-based approach to prevent unauthorised access of network or computer devices. However, ever growing landscape of cyberattacks in recent years has motivated present day researchers to design and develop more accurate …
Published in Current Trends in Information Technology · Vol. 13, Issue 1, 2023 · pp. 1–11 Read article
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A New Framework for Optimal Hesitation Pattern Mining
Abstract: AbstractIn mathematical optimization, the firefly algorithm is a metaheuristic approach. It has been proposed by Xin-She Yang and inspired by the flashing behavior of fireflies. Proposed research used Firefly Algorithm for discovering the best Association rules. In this species, it is always the female who glows, and only the male has wings. In other species, Luciola lusitanica, both male and female firefly may emit light and both have wings. If …
Published in Journal of Communication Engineering & Systems · Vol. 7, Issue 2, 2017 · pp. 34–41 Read article
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Intelligent Document Scanner
Abstract: AbstractThere is an irresistible trend in the present world for scanning the paper documents and convert it into a digitalized format. Most of these scanning treat the whole document as an entire image. In this scenario, we propose a novel “Intelligent Document Scanner” which automatically segment and classify the contents of the image document including texts, tables and images and store it as a PDF document with three sections that …
Published in Journal of Computer Technology & Applications · Vol. 7, Issue 2, 2016 · pp. 47–57 Read article
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Survey of Intelligent Surveillance System using Image Processing and Deep Learning Techniques
Abstract: Abstract Closed-circuit television systems (CCTV) are becoming more and more pop- ular and are being deployed in many offices, housing estates and most public spaces. Thus, the job of CCTV operators is becoming very challenging as the footage contains a lot of information and gradually becomes cumbersome. Rapid advancement in the field of computer vision could be observed as an important trend in video surveillance and lead to substantial effi- …
Published in Journal of Computer Technology & Applications · Vol. 11, Issue 3, 2020 · pp. 34–64 Read article
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Optimization of Thermo-Mechanical Controlled Processing (TMCP) Using Swarm Intelligence
Abstract: In low carbon steel manufacturing, the thermo-mechanical controlled processing (TMCP) has been developed as a grain refinement method that performs a noticeable upgrading in productivity and service performance. Optimizing TMCP by choosing the best strain rate through experiments in labs requires so much effort, time, and cost. In this paper, we developed a new technique based on solving the Zener-Holloman parameter equation via swarm intelligence to get the best strain …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 1, 2023 · pp. 64–69 Read article
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Mental Health and Artificial Intelligence (AI): Marching towards Future
Abstract: One of the most crucial but frequently disregarded facets of our wellbeing is our mental health. In the medical domains of dermatology, radiology, and oncology, artificial intelligence (AI) is being used more and more. AI hasn't been heavily utilised in mental healthcare, though. The need for AI to help identify high-risk individuals and give interventions to prevent and treat mental illnesses is essential due to the high morbidity and mortality …
Published in Research and Reviews: A Journal of Health Professions · Vol. 13, Issue 3, 2023 · pp. 91–95 Read article
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Nasal Medication Conveyance Framework: An Approach for Brain Delivery from Essential to Cutting Edge
Abstract: For the past few years, nasal drug delivery has provided attractive niche to the formulation scientists. It is the first choice as targeted drug delivery when one requires it for brain targeting. In addition, absorption of drug at the olfactory region of the nose provides a potential for a pharmaceutical compound to be available to the central nervous system. The nasal delivery of vaccines is another very attractive application in …
Published in Research and Reviews: A Journal of Medicine · Vol. 6, Issue 1, 2016 · pp. 14–27 Read article
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Farmer Producer Organizations as Catalysts of Rural Transformation: A Multidimensional Framework from Punjab, India
Abstract: Farmer Producer Organizations (FPOs) have evolved as an important institutional mechanism for resolving the socio-economic challenges of small and marginal farmers by fostering collective action, expanding market access, and boosting bargaining power. In the broader context of sustainable rural development, FPOs are increasingly acknowledged as catalysts of rural transformation by contributing to numerous dimensions of farmer well-being. However, current study has generally analyzed FPOs through economic and operational indicators, with …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 2, 2026 · pp. 116–122 Read article
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A Standards-Compliant API Framework for Integrating NAMASTE and ICD-11 TM2 Terminologies into Indian Electronic Medical Records (EMRs)
Abstract: The lack of standardized, interoperable terminology services has hindered the integration of India’s traditional medical systems into the mainstream digital health infrastructure. Although ICD-11 Traditional Medicine Module 2 (TM2) offers an internationally harmonized classification for traditional medicine diagnoses and the NAMASTE portal defines structured vocabularies for AYUSH conditions, current Electronic Medical Record (EMR) platforms in India are unable to natively consume, map, or translate these terminologies in a way that …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 2, 2026 · pp. 19–27 Read article
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Brain Stroke Detection Using Deep Learning and Grad-CAM Explainability Framework
Abstract: Seconds matter when a brain stroke occurs; it is a race against time where rapid, precise intervention is the only way to preserve a patient’s quality of life. This research introduces a deep learning framework designed to act as a vital ally for clinicians, providing automated, high-speed stroke detection through brain MRI analysis. At the heart of our approach is EfficientNetB0, a sophisticated neural network chosen for its ability to …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 8–14 Read article
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Artificial Intelligence for Tracking Cognitive Deviation in Aging Populations: A Comprehensive Review of Techniques, Challenges, and Ethical Concerns
Abstract: Population aging is accelerating worldwide, and with it the burden of cognitive health conditions such as mild cognitive impairment (MCI), Alzheimer’s disease (AD), and dementia. Detecting and monitoring cognitive change early is central to timely intervention, yet conventional diagnostic tools often miss the subtle signals that appear before overt symptoms. Artificial intelligence (AI) has emerged as a promising complement to clinical assessment because it can work through high-dimensional data and …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 27–37 Read article
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From Trace to Truth: Integrating Forensic Science, Analytical Chemistry, Medical Evidence and Artificial Intelligence in Modern Criminal Investigation
Abstract: Modern criminal investigations are inherently interdisciplinary, integrating medical research, forensic science, analytical chemistry, and artificial intelligence (AI) to transform hazy traces into reliable, legally recognised evidence. This study examines the ways in which different domains collaborate across the whole investigation process, ranging from judicial review, laboratory analysis, and computer processing to crime scene management and evidence retrieval. This research is based on a thorough review of scholarly literature and a …
Published in Research and Reviews: A Journal of Toxicology · Vol. 16, Issue 2, 2026 Read article
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Toxicology 4.0: Integrating Artificial Intelligence, Big Data, Health Informatics, and Precision Analytics for Predictive Toxicity Assessment, Real-Time Toxicovigilance, and Personalized Patient Safety
Abstract: Background: Toxicology is undergoing a major transformation, increasingly described as Toxicology 4.0, driven by the integration of artificial intelligence (AI), big data analytics, health informatics, and precision analytics. Conventional toxicity testing is limited by high costs, lengthy timelines, and challenges in translating animal and low-throughput in vitro findings to humans. Aim and Objectives: To comprehensively evaluate the emerging role of Toxicology 4.0 in predictive toxicity assessment, real-time toxicovigilance, and personalized …
Published in Research and Reviews: A Journal of Toxicology · Vol. 16, Issue 2, 2026 Read article
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Speech-Text-Speech Translator: A Generative AI Framework for Real-Time, Identity-Preserving S2S Translation
Abstract: Different languages have been proved a great obstacle to global communication despite the internet's role in allowing information sharing all over the world. While presenting an extensive number of current solutions, traditional Machine Translation (MT) systems are unable to convey complex contextual information and dialects including "Hinglish". Above all, the voice of the interlocutor is lost and is replaced with an artificial one, programmed to mimic the voice of the …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 2, 2026 · pp. 47–57 Read article
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Computational Intelligence and Neuro-Fuzzy Modelling of Polymer Composites: A Critical Review of Performance Prediction and Optimization
Abstract: The increased variety in polymer matrices, reinforcements, fillers, and processing parameters has led to the need to better understand the structure-property, process-property relationships in order to accurately predict and optimize the performance of polymer composites. This paper reviews the applications of computational intelligence methods in polymer composites, with special focus on artificial neural networks, adaptive neuro-fuzzy inference systems, machine learning techniques, and hybrid optimization. The literature is analyzed based on …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Artificial Intelligence and Constitutive Modeling Equations for Predictive Design of High-Performance Polymer Composites
Abstract: Growing polymer composite applications demand accurate mechanical prediction, yet complex interactions and conventional constitutive models limit predictive capability and require extensive calibration. To report these challenges, this research recommends a combined Artificial Intelligence (AI) and constitutive modeling approach based on an Enhanced Tasmanian Devil Optimizer-tuned Residual Neural Network with Multilayer Perceptron (ETDO-ResNet-MLP) for the predictive design of high-performance polymer composites. The study uses a publicly available Polymer Composite Property Dataset …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Graph Neural Networks for Molecular Scale Property Prediction and Inverse Design of Thermoset Polymer Nanocomposites: A Computational Framework
Abstract: Thermoset polymer nanocomposites exhibit properties that are highly sensitive to molecular scale formulation decisions, yet the vast design space remains largely unexplored because of the high cost of experimental characterisation and fully atomistic simulation. This paper presents TNC GNN, a dual mode graph neural network framework developed for the computational design of thermoset nanocomposite formulations. The forward module employs an attention augmented Message Passing Neural Network with 3D geometric encoding …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Carbon quantum dots (CQDs) and bioinspired photonic nanomaterials have emerged as promising multifunctional platforms for a wide range of applications in optoelectronics, nanomedicine, biosensing, fluorescence imaging, and photodynamic therapy. CQDs are nanoscale carbon-based materials characterized by unique optical and electronic properties, including size-dependent photoluminescence, high photostability, excellent water solubility, low cytotoxicity, and remarkable biocompatibility. These characteristics make them attractive alternatives to conventional semiconductor quantum dots for both technological and biomedical applications. Inspired by natural photonic systems such as photosynthetic light-harvesting complexes, rhodopsin-based photoreceptors, butterfly wings, and bioluminescent organisms, researchers have developed advanced nanostructures capable of efficient photon capture, energy transfer, and photoinduced charge separation. Recent advances in synthesis techniques, including hydrothermal, solvothermal, microwave-assisted, and green synthesis approaches, have enabled precise control over the size, surface chemistry, and optical properties of CQDs. Functionalization and heteroatom doping further enhance their photophysical performance and application versatility. In optoelectronics, CQDs have been incorporated into photodetectors, solar cells, light-emitting diodes, and flexible electronic devices due to their tunable emission characteristics and efficient charge transport properties. In the biomedical field, CQDs are increasingly utilized for targeted drug delivery, bioimaging, biosensing, and photodynamic therapy because of their excellent fluorescence behavior and biological compatibility. Furthermore, bioinspired photonic nanomaterials are being explored for artificial photosynthesis and sustainable energy conversion systems, where efficient light harvesting and electron transfer are critical. This review highlights recent developments in the synthesis, photophysical properties, and multifunctional applications of CQDs and related bioinspired photonic nanomaterials, while discussing current challenges and future opportunities for the development of intelligent nanophotonic and bioelectronic technologies.
Abstract: Carbon quantum dots (CQDs) and bioinspired photonic nanomaterials have emerged as promising multifunctional platforms for a wide range of applications in optoelectronics, nanomedicine, biosensing, fluorescence imaging, and photodynamic therapy. CQDs are nanoscale carbon-based materials characterized by unique optical and electronic properties, including size-dependent photoluminescence, high photostability, excellent water solubility, low cytotoxicity, and remarkable biocompatibility. These characteristics make them attractive alternatives to conventional semiconductor quantum dots for both technological and biomedical …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 4, Issue 2, 2026 · pp. 16–24 Read article
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The Influence of Artificial Intelligence on Literary Criticism
Abstract: Artificial Intelligence (AI) has emerged as a significant force in reshaping contemporary literary criticism. Traditionally, the interpretation of literature has relied primarily on human-centered methods such as close reading, contextual analysis, and theoretical framing. However, the integration of AI-based techniques including Natural Language Processing (NLP), Machine Learning (ML), stylometry, and sentiment analysis has introduced new possibilities for examining literary texts at both micro and macro levels. These computational approaches allow …
Published in International Journal of Trends in Humanities · Vol. 3, Issue 2, 2026 · pp. 22–29 Read article