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368 articles for “transformer model”
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The Future of Computing: Exploring the Impact of 3D Technology
Abstract: In the evolving landscape of computing, the integration of three-dimensional (3D) technology has revolutionized various industries, from entertainment to healthcare. “Computers in the 3-D World” explores the transformative impact of 3D computing, focusing on how advances in hardware and software are enabling new forms of interaction, visualization, and simulation. The study explores the key technologies behind this transformation, including virtual reality (VR), augmented reality (AR), 3D modeling, and 3D printing. …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 01–19 Read article
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Enzyme Stability Prediction using BERT and CNN-A Deep Learning Approach for Enhanced Biocatalysis
Abstract: An important factor in determining the efficacy of industrial enzymes used in various biotechnological applications is their stability. The goal of this study is to develop a predictive model for industrial enzyme stability, which is essential to the efficiency of these enzymes in biotechnological applications. The research takes a comprehensive strategy to comprehend the parameters affecting enzyme stability by combining statistical analysis, deep learning algorithms (BERT and CNN), and molecular …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 2, 2024 · pp. 19–35 Read article
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Exploring the Development of AI Models Using Open-Source Tools to Predict Patient Outcomes and Optimize Treatment Plans
Abstract: Integrating artificial intelligence (AI) into healthcare offers a transformative opportunity to enhance patient care and clinical decision-making. Through the use of predictive analytics, AI can significantly enhance the accuracy of outcome predictions and assist in developing personalized treatment plans that cater to each patient’s specific needs. This paper delves into the development of AI models using open-source tools, which are increasingly favored for their accessibility, collaborative nature, and capacity for …
Published in Journal of Open Source Developments · Vol. 11, Issue 3, 2024 · pp. 37–49 Read article
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Machine Learning in Nuclear Medical Applications: A Review of Research Frontiers
Abstract: Nuclear medicine, encompassing PET, SPECT, and targeted radionuclide therapy, generates high-dimensional, quantitative data uniquely suited for machine learning (ML) analysis. This review synthesizes current research applications of ML across six key domains. Positron emission tomography (PET), single-photon emission computed tomography (SPECT), and targeted radionuclide therapy are examples of nuclear medicine modalities that generate high- dimensional, quantitative datasets that are particularly well-suited for machine learning (ML)-driven analysis. These imaging methods provide …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 19–24 Read article
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Development of Automobile Scaled Model from CAD (Blender) Using FDM 3D Printing
Abstract: Additive manufacturing (AM), also known as 3D printing, has emerged as a disruptive technology with the potential to transform automotive manufacturing. This paper reviews the applications of AM across the automotive product development lifecycle. The paper examines case studies demonstrating the use of AM for developing computer-aided design (CAD) models from concept sketches. Overall, AM brings several benefits such as design flexibility, faster time-to-market, and distributed production. However, there are …
Published in International Journal of Advanced Control and System Engineering · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article
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An Analysis of Multimodal Fusion in Deepfake Detection for Video Samples
Abstract: In today’s rapidly evolving digital landscape, deepfake technology stands as both a marvel and a threat to privacy and security. Deepfakes, hyper-realistic synthetic media created using artificial intelligence (AI), can deceive and manipulate on an unprecedented scale, from political propaganda to compromising videos of public figures. This research navigates deepfake detection, focusing on two advanced methodologies: the vision transformers (ViT) image classifier and the Meso4 method. The ViT model utilizes …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 19–27 Read article
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Pathophysiology Reimagined: Integrating Systems Biology and AI for Disease Understanding
Abstract: Pathophysiology, the study of disease mechanisms at molecular, cellular, and systemic levels, has traditionally relied on reductionist approaches that often fail to capture the complex, dynamic, and interconnected nature of biological systems. Diseases such as cancer, neurodegenerative disorders, and infectious diseases arise from intricate interactions among genetic, epigenetic, metabolic, and environmental factors, necessitating integrative, data-driven methodologies for a deeper understanding. Systems biology has emerged as a powerful approach by leveraging …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 63–71 Read article
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Revolutionizing Motorcycle Safety: A Deep Learning Approach for Helmet and Triple Riding Detection using Computer Vision Technology and Machine Learning Model
Abstract: Introducing a revolutionary paradigm in road safety, our project unveils the Intelligent Traffic Surveillance System (ITSS), a groundbreaking initiative poised to transform urban traffic management. In an era where road safety is paramount, ITSS emerges as a beacon of innovation, harnessing the prowess of computer vision and machine learning to tackle two of the most pressing concerns plaguing our roads: helmet non-compliance and triple riding among motorcyclists. At its core, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 1, 2024 · pp. 28–36 Read article
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Fuzzy Probability Distributions and Their Applications in Uncertain Data Analysis
Abstract: This study explores the use of fuzzy probability distributions in data analysis under uncertain conditions, with a specific focus on their implementation in evaluating call center customer satisfaction. Traditional probability models rely on precise parameters, often failing to account for the inherent variability and subjectivity present in real-world data. In contrast, fuzzy probability distributions, which integrate fuzzy logic principles, offer a more adaptable and realistic framework for addressing such complexities. …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 1–8 Read article
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Virtual Reality in Civil Engineering: A Comprehensive Review of Applications, Challenges, and Future Trends
Abstract: Virtual reality (VR) technology has gained significant attention in civil engineering, offering immersive and interactive environments that enhance visualization, safety training, and project management. This review paper comprehensively examines the current applications of VR in civil engineering, focusing on construction safety training, design visualization, and stakeholder collaboration. VR’s ability to simulate hazardous scenarios allows for effective safety awareness and risk mitigation without real-world exposure. Additionally, the integration of VR with …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 3, 2025 · pp. 20–24 Read article
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Artificial Intelligence in Smart Dairy Farming (SDF)
Abstract: Due to increasing demand for quality of milk in dairy farming also for the sustainability, productivity and maintenance of good health of animals. various challenges are faced by dairy farmers and can be addressed using Artificial Intelligence technologies ,By using AI here the individual health ,behavior ,feed management robotic milking and stress free milking system will be implemented .AI technologic implementation will frame the Smart dairy farming in properly and …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 16–20 Read article
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Advances in Multiclass Oral Cancer Detection Using Spectroscopic and AI Techniques
Abstract: Oral cancer, primarily OSCC, is still a major health issue worldwide, especially in low-HDI countries. Early diagnosis is essential since survival rates for early detection are much higher than for late-stage detection. However, traditional methods like visual inspection and biopsy are time-consuming, invasive, and rely on the clinician's skill, which is a limitation in accessibility and efficiency. Oral cancer detection has just been revolutionized by recent advances in spectroscopic techniques, …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 39–48 Read article
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Enhancing Tourism with Augmented Reality
Abstract: The integration of Augmented Reality (AR) technology into the tourism sector has created new opportunities for improving how travelers interact with their environment. This study explores the innovative idea of using AR technology to transform the tourist experience by offering a seamless combination of interactive 3D models, historical information, and navigation assistance. The proposed concept centers on using AR-enabled QR code scanning to provide tourists with an immersive 360-degree exploration …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 2, 2024 · pp. 9–14 Read article
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Monoclonal Antibodies in Next Generation Animal Nutrition: Mapping Nutrient Immune Interaction Networks in Livestock Systems
Abstract: Sustainable livestock production is increasingly constrained by disease pressure, antimicrobial resistance, and declining feed efficiency under intensifying environmental stressors. Conventional nutritional strategies, while essential, remain insufficient to precisely regulate immune function and metabolic resilience. This review explores the emerging role of Monoclonal antibodies as advanced biologics in next generation animal nutrition, with a focus on mapping nutrient immune interaction networks in livestock systems. It synthesizes current knowledge on how nutrients …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 1, 2026 Read article
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Hybrid Numerical–Artificial Neural Network Study of Chemically Reactive MHD Nanofluid Flow Incorporating Thompson–Troian Slip and Stefan Blowing
Abstract: Boundary layer behaviour in chemically reactive nanoliquid is significantly affected by surface conditions, magnetic fields, heat and mas transfer mechanisms. However, the combined impact of Stefan blowing and nonlinear Thompson–Troian slip under inclined magnetic fields remains mostly unexplored, particularly in mixed convection flows. In this research work, the flow of a chemically reactive nanoliquid over a permeable surface is investigated by considering the Troian slip, inclined magnetic fields, Stefan blowing, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 409–425 Read article
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A Review Paper on The Mathematical Foundations of Artificial Intelligence
Abstract: Artificial Intelligence (AI) is deeply rooted in various branches of mathematics, which provide the theoretical foundation and practical tools for developing intelligent systems. This paper explores the crucial role of mathematics in AI, focusing on key areas such as Linear Algebra, Probability and Statistics, Optimization Techniques, Calculus, Graph Theory, and Fourier and Wavelet Transforms. Linear Algebra is fundamental for representing and manipulating data, with applications in dimensionality reduction and neural …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 7–14 Read article
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From Space to Sea: Leveraging Satellite Technology for Monitoring Marine Debris
Abstract: Marine trash endangers ecosystems, so efficient detection is critical. This article describes a novel strategy for improving detection accuracy by integrating YOLOv7 instance segmentation with attention processes. Three models are evaluated: lightweight coordinate attention, the convolutional block attention module (CBAM) for spatial-channel focus, and the bottle neck transformer, which relies on self-attention. On an annotated satellite image dataset, CBAM has the greatest F1 scores in box recognition (77%) and mask …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 1, 2025 · pp. 1–9 Read article
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Employee Well-Being: Deep Learning Approaches to Stress Detection
Abstract: Stress has become a major concern for employee health, productivity, and overall well-being in today's fast-paced work environment. It is a growing global issue, affecting both individual employees and the productivity of organizations. Work-related stress occurs when the demands of a job surpass an individual's ability to manage, whether because of long hours, overwhelming responsibilities, or other pressures. Factors such as conflicts with coworkers or supervisors, constant changes, and job …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 52–58 Read article
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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CFD Analysis: Double Pipe Heat Exchanger, Latent Heat Storage, and BIM-CFD Integration
Abstract: This is a review work covering four research papers. Heat exchangers transport thermal energy across fluids; research in SolidWorks 2014 compared flow simulation to the effectiveness-NTU approach. Slow PCM charging/discharging is a global concern in latent heat storage; research on the influence of flow rate and temperature on melting and solidification durations discovered efficiency in a triple tube heat exchanger design. Advances in computational fluid dynamics for forecasting separated flows …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 2, Issue 2, 2024 · pp. 19–24 Read article