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1974 articles for “Approaches” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Energy-Efficient Design Strategies for Sustainable Machine Tool Development
Abstract: The design of energy-efficient machine tools is essential for promoting sustainable manufacturing, as it addresses the significant energy consumption and carbon emissions generated by these tools in industrial settings. This study investigates innovative design approaches that enhance energy efficiency, with a focus on lightweight materials, improved drive systems, smart control frameworks, and methods for recovering energy. Implementing lighter structural materials allows machine tools to operate with less force, which in …
Published in Trends in Machine design · Vol. 12, Issue 3, 2025 · pp. 30–34 Read article
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Low-cost Machine Learning-Based Sensor-based Activity Recognition for Patients with Financial Difficulties
Abstract: Elderly and schizophrenic patients are compelled to obtain treatment at home due to a lack of resources, putting them at risk for patient neglect and other health issues. This is particularly troublesome for prescription yoga or fitness programs, which are hard for doctors to keep an eye on all the time. We have looked into an automated method that tracks patients’ everyday behaviors using machine learning- based techniques in order …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 3, 2025 · pp. 7–17 Read article
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Phase – Field Modeling of Brittle and Ductile Fracture Under Complex Loading Conditions
Abstract: Phase-field modeling has emerged as a powerful computational framework for predicting fracture behavior in engineering materials, offering a unified description of crack initiation, propagation, branching, and coalescence without the need for explicit crack tracking. This study presents an in-depth examination of phase-field modeling applied to both brittle and ductile fracture under complex loading conditions, including multiaxial stress states, cyclic loading, thermal gradients, and dynamic impact. The phase-field approach regularizes the …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 13–18 Read article
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The Next Era of Solid-State Innovation: Beyond Silicon
Abstract: The semiconductor industry is getting close to the physical and economic boundaries of silicon-based technology. A new era of solid-state innovation is beginning. Beyond Silicon: The Next Era of Solid-State Innovation looks at the materials, device layouts, and manufacturing methods that are about to change the way electronics and energy work. The article talks about improvements in wide- and ultra-wide-bandgap semiconductors, two- dimensional materials, and quantum and neuromorphic systems that …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 19–23 Read article
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Driver Drowsiness Detection System
Abstract: One of the main causes of road accidents worldwide in recent years is driver fatigue. Assessing a driver's mood, or how sleepy they are, is a clear approach to gauge their level of exhaustion. Therefore, detecting driver fatigue is very important to save lives and property. The creation of a prototype drowsiness detection system is the aim of this research. The system operates in real time, continuously capturing images and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 16–21 Read article
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Study to Assess the Effectiveness of Teaching Program on Knowledge Regarding Management of Patients with Regenerative Orthopedics Procedures Among Orthopedic Nurses at Selected Orthopedic Departments
Abstract: Regenerative therapy is an emerging treatment approach in medical science. It focuses on the use of stem cell therapy, biological treatments, tissue engineering, platelet-rich plasma, prolotherapy, and nutraceutical supplements to replace or restore dysfunctional structures or organs. Regenerative therapy emphasizes the body’s natural healing process; it supports physiological healing mechanisms and repairs damaged tissues. It is a minimally invasive approach with expanding applications across various medical fields, including surgery, degenerative …
Published in International Journal of Orthopedic Nursing and Practices · Vol. 3, Issue 2, 2025 · pp. 7–11 Read article
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Livestock and Landscapes: Rethinking Carbon Sequestration Synergies for Transforming Livestock-Raising Paradigm
Abstract: The livestock sector plays a critical role in global agricultural systems, but its impact on climate change is a growing concern due to significant greenhouse gas emissions, particularly methane and nitrous oxide. As the demand for livestock products continues to rise, rethinking current practices becomes essential to mitigate environmental degradation and enhance sustainability. This study examines the synergies between livestock farming and carbon sequestration strategies within global landscapes, with a …
Published in Research & Reviews : Journal of Ecology · Vol. 14, Issue 3, 2025 · pp. 29–43 Read article
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A Review of Torque Ripple Reduction Techniques in Switched Reluctance Motors
Abstract: Switched Reluctance Motors (SRMs) have emerged as a promising alternative to conventional motor technologies due to their rugged structure, low manufacturing cost, high-temperature capability, and suitability for harsh environments. Despite these advantages, the widespread adoption of SRMs in applications such as electric vehicles, household appliances, industrial drives, and aerospace systems is significantly restricted by the issue of torque ripple. Torque ripple manifests as periodic fluctuations in the developed electromagnetic torque, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 45–50 Read article
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Intelligent Water Distribution Management using IoT
Abstract: Water plays a vital role in agriculture, making its efficient management essential for sustainable crop production. However, undetected leaks in irrigation systems can result in significant water loss, irregular watering of fields, soil degradation, and reduced crop yield. Conventional methods like manual inspection are not only labor-intensive but also ineffective in identifying leaks promptly – emphasizing the need for a smarter and automated approach to water monitoring. To address this …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 1, 2026 · pp. 18–27 Read article
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A Review on Microbial Enzymes in the Food Industry: Current Innovations and Future Prospects
Abstract: Over the past few decades, microbial enzymes have become indispensable biocatalysts in food production, fundamentally revolutionizing how we approach manufacturing processes while simultaneously enhancing the quality of what we produce. Today, approximately 200 of the 4,000 known enzymes are deployed commercially with proteases, amylases, lipases, and lactases leading the charge in industrial food applications. This review brings together the latest innovations in how we use microbial enzymes for food processing, …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 15, Issue 1, 2026 · pp. 43–53 Read article
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Early Alzheimer's Disease Detection Using Deep Ensemble Learning and MRI Image Analysis
Abstract: Early detection of Alzheimer's disease (AD) is crucial to slowing cognitive decline and enabling timely clinical interventions. Traditional diagnostic methods, including cognitive tests and single-model classifiers, have limited sensitivity during early stages of the disease. This paper presents a deep ensemble learning approach that integrates multiple convolutional neural networks (CNNs) for accurate Alzheimer's disease detection using structural Magnetic Resonance Imaging (MRI) data. The proposed framework utilizes ResNet50, VGG16, and DenseNet121 …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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New Design Formulae for Safety and Precision in the Fatigue Engineering of Mechanical Components and Structures
Abstract: This paper introduces two new formulae, termed the Nori Fatigue Formulae, for determining the maximum allowable fatigue stress in mechanical components and structures with significant stress concentrations. These formulae will eliminate the usage of code-sensitive safety factors along with other factored values from the entire mechanical design engineering work, ranging from a safety pin to spacecraft. The first formula gives the maximum allowable fatigue stress in tension, and the second …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 6–24 Read article
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Firefly Algorithm–Based Optimization of Processing Parameters for Enhanced Performance of Polymer Composite Materials
Abstract: Polymer composite materials are extensively used in aerospace, automotive, and oil & gas applications due to their high strength-to-weight ratio and design flexibility. However, achieving optimal mechanical and thermal performance strongly depends on precise control of processing parameters such as curing temperature, energy consumption, and material utilization. Conventional trial-and-error approaches often lead to excessive energy usage, non-uniform curing, and sub-optimal composite properties. To address these challenges, this paper proposes an …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 90–107 Read article
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The Impact of Nanotechnology in Transforming Neuro-oncology - A Comprehensive Review
Abstract: The treatment of central nervous system (CNS) tumours, including aggressive malignancies like glioblastoma, faces significant challenges. The blood–brain barrier (BBB) blocks nearly 98% of small-molecule drugs from achieving therapeutic levels in the brain, and the heterogeneity of these tumours frequently contributes to treatment resistance and poor outcomes. Traditional approaches, including chemotherapy and radiotherapy, are hindered by systemic toxicity and inadequate drug penetration. Nanotechnology provides a promising alternative, as nanoparticles (NPs) …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 627–637 Read article
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Systematic Review of Application of Nature-Inspired Algorithms for Resource Optimization in Multi-Programmed Operating Systems
Abstract: Multi-programmed operating systems are increasingly confronted with complex challenges in efficiently managing system resources, primarily due to the need to handle numerous concurrent processes with diverse and often conflicting resource demands. As these systems evolve, ensuring optimal performance across various dimensions, such as CPU scheduling, memory allocation, and load balancing, has become crucial. In this context, nature-inspired algorithms have emerged as promising solutions for enhancing resource optimization. These algorithms, which …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 08–14 Read article
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ML Model Comparison for Sentiment Analysis Across Diverse Datasets
Abstract: Analyzing sentiment is crucial for understanding public opinion on various issues in marketing, politics, and social sciences. This study compares the performance of seven different machine learning algorithms for sentiment classification, focusing on their effectiveness, accuracy, and complexity. The research is conducted on a pre-processed dataset with balanced text samples, utilizing feature extraction methods such as Term Frequency-Inverse Document Frequency (TF-IDF). The performance assessment criteria consist of accuracy, precision, recall, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 26–33 Read article
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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 Read article
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Artificial Intelligence and IoT Integration for Real-Time Violence Monitoring
Abstract: The peace and tranquility of any place can be affected greatly by the insurgence of violence and violent attacks that are perpetrated by individuals with malicious and nefarious intentions. These individuals terrorize the areas and can cause a lot of harm and damage to people and public property. The incidences of violence are undesirable and can be problematic to handle by the law enforcement agencies, as these acts are committed …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 39–45 Read article
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Skin Disease prediction and classification from dermoscopy images using Neural Network
Abstract: Skin diseases are among the most common health-related problems affecting people of all age groups, and their occurrence often varies with seasonal and environmental conditions. Delayed or incorrect diagnosis of skin disorders can lead to severe complications, making early and accurate detection extremely important for effective treatment and prevention. In recent years, rapid advancements in deep learning and neural network technologies have significantly contributed to the development of automated medical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Paediatric Epilepsy: Current Advances in Diagnosis and Management
Abstract: Paediatric epilepsy is one of the most common chronic neurological disorders of childhood, characterised by recurrent unprovoked seizures resulting from abnormal neuronal activity. Accurate diagnosis is essential and is based on a detailed clinical history, seizure semiology, neurological examination, and electroencephalography (EEG), with neuroimaging such as magnetic resonance imaging (MRI) used to identify structural abnormalities. Classification according to seizure type and underlying aetiology genetic, structural, metabolic, immune, infectious, or unknown—guides …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 1, 2026 · pp. 53–68 Read article