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1089 articles for “data modelling”
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Applying Text Analysis Methods for Emotion Recognition
Abstract: This article presents a comprehensive study of sentiment analysis, a vital task in the realms of natural language processing (NLP) and artificial intelligence (AI). Sentiment analysis involves the extraction and classification of subjective information from textual data, determining whether the sentiment expressed is positive or negative. This paper investigates different approaches and methodologies used in sentiment analysis, encompassing machine learning models as well. Additionally, it discusses the challenges faced in …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 2, 2024 · pp. 12–22 Read article
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Smart Agriculture in India: Advancements in Image Processing for Automated Plant Disease Detection and Crop Analysis
Abstract: The adoption of image processing technologies in agriculture is emerging as a revolutionary method for tackling persistent challenges in the farming industry. These techniques are increasingly used for different tasks such as detecting plant diseases, assessing crop health, and predicting yields, especially in the framework of smart agriculture systems. This study paints a detailed picture of the latest progress in image processing techniques applied to automated disease detection and detailed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 13–19 Read article
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AI and ML-Driven Immersive Technologies: A New Era in Education
Abstract: The very fast adoption of Artificial Intelligence (AI) and Machine Learning (ML) in education has transformed contemporary teaching and learning ecosystems driven by advances in immersive technologies and the growing engagement of global technology leaders with virtual environments. AI-powered educational platforms enable adaptive and personalized learning pathways by dynamically adjusting content, pace and instructional strategies to learners’ preferences, abilities and learning styles by improving engagement, retention and academic outcomes. Deep …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 116–123 Read article
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Geo AI-Powered Urban Footprints
Abstract: In the contemporary era, building footprints are of paramount importance for accurate and current inventories in the development of infrastructure and geospatial analysis. Traditional methods, relying on manual digitization, were largely unsustainable as the urban regions were growing rapidly. Manual digitization was expensive and lacked geometric precision. This paper introduces an automated, end-to-end GEO AI-powered framework for high-end fidelity building footprint extraction from Google Satellite Data. Our approach for this …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 2, 2026 Read article
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Advanced Private Cloud Security and Privacy Preservation Through the Integration of Machine Learning and Cryptography
Abstract: In modern technological landscapes, private cloud security is of paramount concern due to the ever-increasing volume and complexity of cyber threats. This research work explores the integration of machine learning and cryptography to enhance security within private cloud environments. This study aims to mitigate vulnerabilities that may compromise data integrity, confidentiality, and availability in private cloud infrastructures by using machine learning algorithms and strong cryptography. By detecting anomalous cloud patterns …
Published in International Journal of Advanced Control and System Engineering · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article
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Improving The Accuracy of Medical Diagonosis Detection Using Machine Learning
Abstract: While accurate and timely medical diagnosis is a fundamental aspect of effective health care delivery, traditional methods have not been able to overcome major hurdles such as inefficiencies in data analysis with Gi Human Error as well as limitations in scalability. The “Improved Accuracy of Medical Diagnosis Detection Using Machine Learning” project seamlessly integrates advanced machine learning (M L) technologies with efficient preprocessing and feature selection techniques to outperform all …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 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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Tribological Behaviour of PTFE based Composite Materials with Different Filler Materials: A Combine Numerical and Experimental Approach
Abstract: This study investigates the tribological behaviour of Polytetrafluoroethylene (PTFE) composites reinforced with various fillers, utilizing the Archard wear model to analyse wear mechanisms and predict wear rates. PTFE is widely recognized for its excellent chemical resistance and low friction, but its inherent wear resistance is relatively poor. To enhance its tribological properties, fillers such as glass fibres, carbon fibres, bronze, and graphite were incorporated into the PTFE matrix. In the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 547–557 Read article
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Personalized Nutrition and Exercise: Pioneering the Path to Precision Medicine
Abstract: Preventive healthcare is about to undergo a major shift thanks to the personalised exercise and nutrition paradigm, which is based on precision medicine concepts. In order to create tailored recommendations for improving health outcomes and preventing chronic diseases, this article explores the integration of genetic profiling, metabolic evaluation, and lifestyle factors. A person's response to food and exercise depends heavily on genetic and metabolic variances, which emphasises the need of …
Published in Emerging Trends in Personalized Medicines · Vol. 1, Issue 2, 2024 · pp. 42–46 Read article
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Advancements in AI-Driven Diagnostics for Dental Health: A Comprehensive Review
Abstract: Dental diseases, also known as oral diseases or dental conditions, encompass a range of health problems affecting the teeth, gums, mouth, and associated structures. These conditions can lead to pain, discomfort, and severe complications if left untreated. Early detection and accurate diagnosis are crucial for effective treatment and prevention of further complications. This comprehensive literature review aims to identify common dental problems such as Tooth Decay (Cavities), Gingivitis, Periodontitis, and …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 1–7 Read article
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Comparative Proteomics: From Cell Lines to Clinical Samples
Abstract: Comparative proteomics is a powerful tool for understanding the molecular differences between various biological samples. It entails identifying and measuring proteins in complex biological samples to assess their abundance, modifications, and interactions under various conditions. This approach plays a crucial role in advancing biomedical research, especially in disease understanding, biomarker discovery, and therapeutic development. While cell lines are widely used for proteomic studies due to their controlled environments and reproducibility, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 30–34 Read article
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The Digital Frontier: How Computers Are Shaping the Future of Space Exploration
Abstract: The integration of computers and space technology has revolutionized the way we explore and understand space. Advanced computing systems play a pivotal role in space missions, from spacecraft navigation and communication to data processing and analysis. These technologies enable accurate modelling, simulation, and mission planning, allowing scientists and engineers to overcome the challenges of space exploration. Computers have also facilitated innovations such as artificial intelligence in autonomous spacecraft and real-time …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 1, 2025 · pp. 1–10 Read article
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Melanoma Skin Cancer Detection Using Deep Learning
Abstract: Melanoma, a fatal type of skin cancer, is a major global health concern. For better patient outcomes, early and precise detection is essential. A branch of artificial intelligence called deep learning has demonstrated encouraging outcomes in medical image analysis, particularly the identification of skin cancer, in recent years. We present a new method for detecting melanoma skin cancer in this paper by utilizing the ResNet-50 architecture, a deep convolutional neural …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 · pp. 1–9 Read article
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Simulation and Experimental Analysis of Heat Treatment for Steel Tie Rods: A Review
Abstract: The study is related to the actual heat treatment and simulation of the physical deformation of the steel tie rod and compares the observations for process optimization. The general methodology is to go for either traditional or induction hardening after getting the chemical composition of the material, followed by tempering, which is a key technique for improving the mechanical properties of materials, strength, hardness, etc., and to release stresses. This …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 43–51 Read article
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Green Fabrication of Glutaraldehyde-Crosslinked Chitosan/PVA Biocomposite for Heavy Metal Removal from Wastewater
Abstract: Chitosan (CS) and Polyvinyl alcohol (PVA) are polymers that possess biodegradable, biocompatible, and non-toxic properties, making them suitable for wastewater treatment applications. The primary objective of this research is to chemically modify chitosan in a novel manner to enhance its ability to remove hexavalent chromium Cr(VI) from aqueous solutions. In this study, a composite material was synthesized by crosslinking PVA and CS with glutaraldehyde (GA), resulting in the formation of …
Published in Journal of Water Pollution & Purification Research · Vol. 12, Issue 3, 2025 · pp. 59–83 Read article
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Hyper Personalization Using AI: Elevate Fitness
Abstract: In the modern era, many individuals find it challenging to prioritize their health and well-being due to busy lifestyles filled with work, academic, and personal obligations. Conventional fitness and nutrition programs often apply uniform strategies that overlook individual differences in body type, preferences, and goals. This lack of real-time feedback and contextual customization often leads to poor user engagement and unsatisfactory results over time. Elevate is a comprehensive, AI-powered fitness …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 · pp. 10–21 Read article
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AI-Based Cybersecurity Framework for Protecting Smart Surveillance Infrastructure in Mumbai
Abstract: Smart city infrastructures increasingly rely on interconnected surveillance systems to ensure safety, operational efficiency, and public trust. However, the rapid expansion of IoT-based monitoring technologies has introduced new cyber risks, especially in high-density metropolitan areas. This paper proposes an AI-driven cyber resilience framework targeting smart surveillance infrastructure as a critical smart-living domain, focusing on Mumbai as a case study. Using the CIC-IDS2017 dataset, a machine learning-based intrusion detection model is …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 Read article
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Optimizing Marketing Campaigns Using Random Forest and A/B Testing
Abstract: Marketing initiatives play a vital role in driving business growth by reaching targeted consumer segments through tailored strategies across multiple channels. The success of these initiatives is influenced by various factors, including the type and duration of the campaign, the characteristics of the target audience, the communication channels employed, and the overall efficiency of each strategy. These factors collectively impact key performance metrics such as conversion rates, customer acquisition costs, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 01–09 Read article
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AI-Enabled Linear Regression Model for Spectroscopic Milk Adulteration Analysis
Abstract: Milk adulteration poses a serious threat to public health and quality assurance in the dairy industry. This requiring rapid, reliable, and non-destructive detection techniques. This study presents a linear regression-based analytical model for identifying and quantifying milk adulteration using spectroscopic data. Spectral measurements of milk samples, including both pure and adulterated variants were acquired using spectroscopic techniques at relevant wavelengths.Blending of other components in pure milk , is specifically called …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 15, Issue 1, 2026 · pp. 28–42 Read article