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960 articles for “Machine Learning”
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Copper Sulfide Semiconducting Nanoparticles for Antibacterial Applications: Synthesis Strategies, Mechanisms and Performance – A Review
Abstract: Copper sulfide nanoparticles (CuS NPs) have drawn growing attention as a next-generation antibacterial platform, owing to their tunable structural, optical, and catalytic properties. This review consolidates current evidence on CuS NP synthesis, mechanisms, and antibacterial performance, comparing chemical and green synthesis routes alongside the effects of morphology, doping, and surface modification. Mechanistically, CuS NPs act through several overlapping pathways, including reactive oxygen species generation, bacterial membrane disruption, ion release, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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A Factorial Investigation of Hyperparameter Tuning Strategies for Lasso- Based Genomic Prediction
Abstract: In an earlier comparative study of machine-learning methods for genomic prediction of wheat grain yield, we reported a counter-intuitive result: automated nested-cross-validation tuning of the Lasso regularization penalty reduced mean predictive ability relative to a fixed, arbitrarily chosen penalty (mean Pearson r falling from 0.408 to 0.349 across four environments), the opposite of the expected effect of hyperparameter tuning. We hypothesized two possible explanations at the time — high-variance penalty …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Self-Healing Structural Polymer Composites Incorporating Bio-Inspired Nanofillers
Abstract: Self-healing polymer composites become an attractive family of intelligent materials that are capable of autonomously repairing damage, which will enhance their durability, reliability and service life in extreme engineering applications. The materials are based on the principles of nature, using the nanofillers that are derived from biological systems to improve mechanical properties and self-healing capabilities by utilizing hierarchical structures and multifunctional interface interactions. The recent developments on the formulation of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Reinforcement Learning for Adaptive Sensing with Shape Memory Polymer-Based IoT Nodes
Abstract: The rapid expansion of intelligent sensing in the Internet of Things (IoT) has revealed the pressing need for materials and algorithms capable of self-adaptation in volatile environments. Conventional polymer-based sensors and static control strategies often fail to capture nonlinear thermo-mechanical dynamics, leaving them unsuitable for unpredictable operating conditions. Although prior studies have improved polymer composites or introduced algorithmic optimization independently, few attempts have coupled the adaptability of smart materials with …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 370–391 Read article
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Humanoid AI Robot: A Member of Our Next-generation Family
Abstract: Humanoid robots represent a swiftly advancing area of study and innovation, seeking to produce robots with traits and abilities resembling those of humans. These robots have diverse uses, such as aiding humans in different activities or exploring dangerous or inaccessible areas. Advancing humanoid robots entails combining cutting-edge technologies, including robotics, natural language processing, computer vision, and artificial intelligence. Combining computer science and engineering, robotics is an interdisciplinary subject of study. …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 1, 2024 · pp. 20–24 Read article
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A Comprehensive Review of CNN-Based Framework for Multi-Sign Detection of Diabetic Retinopathy in Fundus Images Using Public Datasets
Abstract: Diabetic retinopathy (DR) is one of the main causes of vision impairment. Blindness prevention and effective treatment depend on early detection. A thorough deep learning-based framework for the automatic segmentation and simultaneous detection of exudates, hemorrhages, and microaneurysms – three important DR indicators – from retinal fundus images is presented in this work. These three pathological signs’ corresponding annotated image patches, along with background (no-sign) areas, were used to train …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 14–23 Read article
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Sign Language and Face Expression Recognition Using Neural Networks: Deep Learning Approach to Break Communication Barriers
Abstract: Our study proposes a multimodal gesture recognition system specifically designed to aid communication for the deaf community. By employing neural network concepts, we utilize 3D convolutional neural networks (3D CNNs) to extract features from both hand and face images, focusing on relevant regions. Preprocessing techniques are applied to isolate these areas of interest prior to feature extraction. Unique 3D CNN architectures are then trained for each modality to capture the …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
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Google Play Store Analysis
Abstract: Google play store consists of millions of applications and several thousand apps are added on the play store every day. The competition is so fierce that it is really difficult for the developers to find out whether the app that is the product of his hard work is going to be successful or not. The main goal of the study is to create a tool that helps developers and organizations …
Published in Journal of Open Source Developments Read article
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Transformative Digital Learning Through AI Technologies
Abstract: The progress of artificial intelligence (AI) has brought about a remarkable change in the educational system. It has paved the way for the development of new educational paradigms like adaptive, personalized, and data-driven digital learning environments, replacing the old ones which were more or less teacher-cantered. In the new digital world, AI technologies have become the main drivers for educational systems to go digital and for human teachers to shift …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 Read article
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Paradigm of Artificial Intelligence in Business Management
Abstract: Artificial intelligence stands out as a prominent trend in today's technological landscape, enabling machines to engage in human-like thinking, learning from experiences, adapting to new inputs, and making decisions. This capability facilitates rapid and error-free results, akin to human rational decision-making. In the contemporary business landscape, which is often regarded as a cornerstone for national development, artificial intelligence plays a pivotal role. Businesses, ranging from small-scale enterprises to medium-sized ones …
Published in Current Trends in Information Technology · Vol. 14, Issue 1, 2024 · pp. 26–30 Read article
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Dynamic Performance Enhancement of Polymer Composites through Metaheuristic machinining optimization
Abstract: This work aims to provide an optimization of meta-heuristic algorithms in order to improve the dynamic behavior of composite materials utilized in various practical engineering tasks. Based on the Comprehensive literature review it has been observed that composite sandwich panels with PVC foam cores accomplished mechanical characteristics superior than those ones that were produced on PU foam core mainly in flexural, compression, and impact tests Thus the study establishes the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 114–129 Read article
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Artificial Intelligence in Cerebellum Activation
Abstract: Neuroscience plays a significant function during the progression of artificial intelligence. It provided inspiration for the development of human-like AI. There are two ways that neuroscience encourages us to develop AI systems. Neural networks that replicate human cognition and those that match the structure of the brain are the two objectives. Neural networks, which draw inspiration from the architecture of the human brain, are the engine behind contemporary artificial intelligence …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 14–26 Read article
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Facial Recognition System Utilizing Real-time Deep Learning Techniques
Abstract: This research introduces an openly accessible deep learning-based framework designed for facial recognition. The system encompasses five key stages: face segmentation, detection of facial features, face alignment, embedding, and classification. Deep learning methods are employed for the extraction of fiducial points and embedding within the system. For the classification task, a Support Vector Machine (SVM) is utilized due to its efficiency in both training and inference phases. Notably, the system …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 14–20 Read article
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Assessment of Milk Quality Optimization of Yogurt Fermentation
Abstract: In the creation of new products, yogurt makers need to prioritize consumer preferences to enhance their market share. An advanced prediction method will help in grasping the fundamental connection between consumer preferences and sensory attributes. This study introduces a new deep learning approach that employs an autoencoder to derive product features from expert-scored sensory attributes. These sensory features are then analyzed through support vector machine regression to align them with …
Published in Research and Reviews : Journal of Dairy Science and Technology · Vol. 13, Issue 2, 2024 · pp. 6–12 Read article
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War Between Robots and Humans: Evolution of Robots and Disasters Associated with Them
Abstract: Robotics and artificial intelligence (AI) have transformed the landscape of technology, allowing machines to take on roles that were previously thought to require human intelligence and skill. From industrial automation to military applications, the integration of intelligent robots into human society presents unprecedented benefits and equally significant risks. This paper investigates the historical evolution of robotics, the deepening human dependency on machines, and the emerging threats that suggest a potential …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 44–51 Read article
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The Cybernetics Perspective of AI
Abstract: The complicated connection between cybernetics and AI is investigated in detail in this study. The focus was on the cybernetic basis of AI, specifically the part that control systems and feedback loops play. Norbert Wiener was one of the founders of cybernetics, which is important for understanding how machines and animals direct and talk to each other. It explains the basic ideas that have led to the progress in AI, …
Published in Journal Of Network security · Vol. 12, Issue 1, 2024 · pp. 26–30 Read article
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AI-Driven Prediction of Square-Hole Laser Trepanning Performance in AA7075/15%SiC/15% Glass Fiber Hybrid Composites Using Taguchi–ANOVA and Deep Neural Networks
Abstract: Hybrid AA7075 composites reinforced with 15% silicon carbide (SiC) and 15% glass fiber were fabricated via the stir casting technique to improve machining and structural performance. The addition of dual reinforcements into the aluminum matrix was aimed at enhancing hardness, thermal stability, and surface quality during non-traditional drilling operations. Square-hole drilling was performed using a laser trepanning process, and the key responses—hole size accuracy, surface roughness, and taper angle—were systematically …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1932–1943 Read article
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Integrating Digital Twins, Smart Materials, and Human Machine Collaboration for Sustainable Smart Manufacturing: Smart CNC & Industry 4.0 Applications
Abstract: The rapid evolution of Industry 4.0 and the emerging transition toward Industry 5.0 have been catalyzed by the convergence of intelligent digital technologies such as digital twins, cyber–physical systems (CPS), artificial intelligence (AI), the Internet of Things (IoT), and human-in-the-loop (HITL) frameworks. These technologies have transformed traditional manufacturing into adaptive, data-centric ecosystems capable of real-time optimization and predictive decision-making. In recent years, the fusion of computer numerical control (CNC) machines, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
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Intensifying Security with Smart Video Surveillance
Abstract: The smart video surveillance system is designed to observe the activities of people nearby for safety concerns. This smart video surveillance can be installed at malls, public areas, banks, businesses, and ATM machines. The field of network surveillance research is rapidly expanding. The cause for this is the global insecurity that is occurring in great extent. As a result, an intelligent monitoring system that gathers data in real time, communicates, …
Published in Recent Trends in Programming languages Read article
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Cybersecurity of AI and IoT Integrated for Mechanical Industries
Abstract: By facilitating the concept of Industry 4.0, the intersection of artificial intelligence (AI) and the Internet of Things (IoT) has changed the mechanical industries. When combined, these technologies are advancing process optimization, predictive maintenance, real-time condition monitoring, and smarter automation. In order to give proactive system control and intelligent decision-making, AI algorithms mine large datasets generated via IoT devices for relevant patterns. In the meanwhile, IoT guarantees smooth communication between …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 27–33 Read article