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83 articles for “pattern extraction”
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Screening of the used pattern of Kokilaksha (Asteracantha longifolia Nees.) containing formulations through Ayurved compendium
Abstract: Ayurveda is the science of life, addresses the holistic perspective on well-being. It encompasses the pathology and numerous physiologies of diseases, along with their therapies. According to conventional medicine, plant extracts have been used to treat a number of illnesses since antiquity. Therefore, research on traditionally used medicinal plants is significant for two reasons: first, it might lead to the development of novel chemotherapy-related drugs; and second, it might provide …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 10, Issue 3, 2023 · pp. 6–16 Read article
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VolleyNexis AI: A Multimodal Artificial Intelligence Framework for Opponent Strategy Prediction, Tactical Intelligence, and Athlete Performance Optimization in Volleyball
Abstract: The rapid advancement of Artificial Intelligence (AI) has profoundly transformed sports analytics, enabling deeper insights, real-time data analysis, and enhanced performance predictions. Noticeable results have been seen by enabling automated analysis of complex gameplay patterns along with athlete performance. Volleyball is a dynamic and strategic sport, which requires continuous tactical adjustments and constant monitoring of the player’s performance. This paper presents VolleyNexis AI, which is a multimodal artificial intelligence framework …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 2, 2025 Read article
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Performance Evaluation of Green Walnut Husk Waste Extract for Inhibiting Aluminium 8088 Corrosion in Acidic Solution
Abstract: The cumulative call for environmental and supportable corrosion inhibitors has obsessed curiosity in exploiting plant-based agronomic surplus resources. Presented research work discovers the corrosion inhibition probable of green walnut husk extract(GWH)—a normal and plentiful agro-waste—on Aluminium 8088 alloy in an acidic medium. Aluminium 8088, however identified for its corrosion resistance, is vulnerable to squalor in highly acidic settings, affectation trials in several industrial claims. GWH extract act as an ecologically …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 45–59 Read article
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Live Integrated Facial Observation (L.I.F.O.)
Abstract: A human face is the most influential part of humans that can uniquely identify a person. Using all the facial characteristics as biometric, the LIFO system can be applicable in many different ways. Like in everyday life, the most mandatory task in any organization is attendance marking. Earlier, people used to mark their presence using paperwork but now along with the advancement of technology, this system has also changed and …
Published in Journal of Advancements in Robotics Read article
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Harnessing Deep Learning to Explore Microbial Community Structure and Carbon Storage Capacity in Mangrove Ecosystems: A Framework for Computationally
Abstract: Mangrove ecosystems represent one of the most efficient natural carbon sinks on Earth, functioning as critical blue carbon habitats that sustain diverse microbial communities responsible for biogeochemical cycling and long-term carbon storage. Despite their global ecological significance, accurately quantifying and predicting carbon sequestration in mangrove systems remains challenging due to the complex interactions between microbial diversity, sediment chemistry, and environmental drivers. This study presents a comprehensive and sustainable artificial intelligence …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 41–49 Read article
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Explainable GeoAI-Based Multi-Temporal Remote Sensing Framework for Early Detection of Climate-Induced Land Cover Transformation
Abstract: Climate change has emerged as one of the primary drivers of rapid land cover transformation, affecting ecosystems, agricultural productivity, biodiversity, and regional sustainability. Traditional remote sensing approaches often face challenges in detecting subtle and early-stage land cover changes due to limitations in temporal analysis and model interpretability. This study proposes an Explainable GeoAI-based multi-temporal remote sensing framework for the early detection of climate-induced land cover transformation using multi-source satellite imagery …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 2, 2026 Read article
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Classification and Detection of Brain Tumor using Convolutional Neural Network
Abstract: Tumors are masses created when brain cells multiply uncontrollably. A brain tumor is the medical term for this condition. Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Developing a treatment plan is essential to raising a patient's standard of living. Tumors in different regions of the body are evaluated using a variety of imaging techniques, with MRI pictures being utilized mostly for …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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IOT and algorithmic intelligent motor health monitoring as well as maintenance prediction
Abstract: Manufacturing, transportation, and energy systems rely largely on industrial electric motors, and their untimely failure can result in expensive downtime, safety hazards, and decreased operational efficiency. The majority of traditional motor maintenance procedures rely on reactive methods or routine inspections, which frequently miss early-stage problems and lead to needless maintenance or unexpected breakdowns. This project offers an Intelligent Motor Health Monitoring and Predictive Maintenance System that combines Internet of Things …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 28–37 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Pedestrian Gait Parameter Measurement Using a Cascade of Edge and Corner Detection Technique
Abstract: ABSTRACTMost modern surveillance systems currently rely upon Closed Circuit TV feeds monitoring system. This report documents a new approach towards automating pedestrian recognition within typical video footage. The proposed work shows how the gait parameters can be measured from the video footage using the mathematical theory of Geometry and computer vision and pattern recognition technique which can be further used for recognize individuals. When people walk normal to the viewing …
Published in Journal of Computer Technology & Applications · Vol. 1, Issue 1-3, 2011 · pp. 75–88 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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Fake Product Detection Using Convolutional Neural Networks
Abstract: The widespread circulation of counterfeit products in global markets presents a significant threat to both consumer trust and the integrity of established brands. With the advancement of artificial intelligence, particularly deep learning, there is growing potential to develop more sophisticated systems to combat this issue. This study introduces a novel counterfeit detection framework using the VGG16 Convolutional Neural Network (CNN) to distinguish between authentic and counterfeit products through image analysis. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 08–15 Read article
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Quantitative Image-Based Assessment of Degradation Patterns in Polymer-Based Medical Implants
Abstract: Polymer-based medical devices are widely used in clinical practice, where long-term material degradation can compromise performance and patient safety. Traditional polymer degradation studies predominantly rely on laboratory-based experiments, which often fail to capture real-world operational and usage conditions. In this study, a multimodal, data-driven framework is proposed for the quantitative assessment of degradation patterns in polymer-based medical devices using publicly available clinical failure data. Structured operational parameters, including cumulative usage …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1510–1518 Read article
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Silver Particles coating on polypropylene matrix for bacterial filter property
Abstract: Silver particles have a wide range of biomedical applications, including their use as drug. In this paper, we report on the synthesis of silver particles using crude aqueous extract of Manihot esculenta leaf extract. Two different (conventional stirring and ultrasonic) methods were employed in the reduction of AgNO3 process. Native extract as well Ag colloidal extract were checked cytotoxicity against Human Cervical Carcinoma cell. The anti cancer results achieved excellent …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 7, Issue 3, 2020 · pp. 16–25 Read article
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Analysis of impact of Meditation on Cognitive Workload using EEG Signals
Abstract: AbstractMental activities can be indicated by the Cognitive workload which are useful in applications like Biomedical, Human Machine Interaction and Task analysis. The mental effort applied on the Working memory at a certain given time is commonly known as Cognitive load. The EEG Signals of Cognitive Workload can be studied and classified. The features such as Entropy, Energy, Power, etc. can be extracted from the EEG signals and processed using …
Published in Current Trends in Signal Processing · Vol. 10, Issue 1, 2020 · pp. 29–39 Read article
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Assessing the Performance of DL Methods in Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a computer vision task that involves the automatic identification and classification of hand-written digits. The objective is to develop models capable of accurately recognizing and distinguishing digits handwritten by humans. With the development of machine learning and deep learning techniques, this field has advanced remarkably. The convolutional neural network (CNN) is the most often used technique for this purpose. By utilizing CNN, the model can learn …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 25–32 Read article
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Green Synthesis and Functional Evaluation of Ag–Polypyrrole/TeO2 Nanocomposites for Advanced Electronic Applications
Abstract: Ag–PPy/TeO₂ nanocomposites with TeO₂ loadings ranging from 2% to 10% were synthesized using an in-situ chemical polymerization method. Green tea extract, rich in phytochemicals, acted as both a reducing and stabilizing agent to facilitate the formation of metal oxide nanoparticles. The structural and morphological characteristics of the nanocomposites were analyzed using FTIR, PXRD, and SEM techniques. FTIR confirmed the successful integration of Ag, TeO₂, and PPy functional groups. PXRD patterns …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 64–76 Read article
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Identifying and Implementing a Machine Learning Model Suitable for Processing Visually Evoked Potential
Abstract: A Brain-Computer Interface (BCI) is a system that translates brain activity patterns into computer commands, bypassing physical movement. Electroencephalography (EEG) is commonly used to acquire signals in BCI research. Visual evoked potentials (VEPs) are brain responses in the visual cortex to visual stimuli. Recent studies show that exposing individuals to flickering at a consistent frequency generates EEG signals synchronized with the stimulation. Efficient extraction of VEP signals begins with preprocessing …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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Image-Based Evaluation of Implant Tissue Interface Integrity in Polymer Orthopaedic Devices
Abstract: Polymer orthopedic implants offer radiolucency and mechanical compatibility with bone, but long-term success depends on maintaining a stable implant–tissue interface. Routine imaging is widely available for follow-up, yet interface integrity is commonly judged qualitatively, limiting early detection of fixation compromise and reducing comparability across devices and time points. This work presents an image-based methodology to quantify interface integrity by extracting interpretable interface descriptors from a standardized interface belt around the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 170–179 Read article