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1045 articles for “U-net”
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Virtual Machine Cost & Computing comparison between cloud service
Abstract: Cloud computing has revolutionized enterprise IT infrastructure with virtual machines forming the cornerstone of Infrastructure as a Service deployment. This study provides a detailed comparative evaluation of virtual machine pricing and computational performance among three leading cloud computing platforms: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). Through quantitative analysis of current pricing data from September 2025, independent performance benchmarks from Cockroach Labs 2021 Report, and market …
Published in International Journal of Mobile Computing Technology · Vol. 4, Issue 2, 2026 Read article
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Eco-Efficient Skies: Life Cycle Assessment and Carbon Footprint Minimization of Fiber-Reinforced Polymer Composites in Aerospace Application
Abstract: The increasing integration of fiber-reinforced polymer (FRP) composites in aerospace structures necessitates a rigorous evaluation of their environmental sustainability throughout their entire life cycle. This study presents a comprehensive life cycle assessment (LCA) and carbon footprint analysis of carbon fiber-reinforced polymer (CFRP) and glass fiber-reinforced polymer (GFRP) composites applied to structural and semi-structural components in commercial aerospace applications. Following ISO 14040/14044 standards and employing the ReCiPe 2016 Midpoint (H) impact …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 147–160 Read article
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Biopolymer–Cement Hybrid Panels from Recycled Paper Mill Reject: Experimental Characterisation and Machine Learning Optimization
Abstract: The increased rate of the accumulation of industrial residues in the developing countries is a major cause of concern for the environment. The current study brings forth the use of industrial residues in the form of the production of eco-friendly building materials as a sustainable approach to their valorization. The valorization of recycled paper mill reject, a cellulose-based biopolymeric industrial residue, is being addressed in this study as a reinforcement …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 67–90 Read article
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Scaling of Machine Learning Techniques in Medical Imagining and Biomedical Applications Concerning Healthcare
Abstract: Machine learning refers to a field within computer science enabling computers to learn without explicit programming. Stemming from artificial intelligence's study of pattern recognition and computational learning theory, machine learning develops algorithms capable of learning from vast datasets and making predictions. Its applications span diverse computing tasks like email filtering, network intrusion detection, optical character recognition, and computer vision, where conventional algorithm design proves challenging. Notably, in computer vision, a …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 41–44 Read article
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Generative AI-Based Inverse Design of Sustainable Biodegradable Polymers with Target Mechanical and Thermal Properties
Abstract: The escalating global plastic pollution crisis has intensified the urgent need for sustainable biodegradable polymer alternatives that can match or exceed the performance of conventional petroleum-based plastics while minimizing environmental impact. However, traditional polymer discovery approaches are severely constrained by high experimental costs, protracted development cycles spanning years, and fundamental inability to simultaneously optimize multiple conflicting material properties such as mechanical strength, thermal stability, and degradation kinetics. This study presents …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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ML-Driven Defect Detection in Additive Manufacturing of Polymer Composites Using Thermal Imaging
Abstract: Polymer-based flexible biosensors have emerged as a pivotal technology in continuous health monitoring, yet their deployment in real-world settings is often hindered by undetected micro-defects and signal distortion caused during fabrication or usage. Existing diagnostic frameworks typically rely on post-hoc processing or bulky instrumentation, failing to offer scalable, real-time detection during additive manufacturing workflows. This study introduces an end-to-end, thermographic imaging-integrated framework for in-situ defect identification during the additive manufacturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 201–215 Read article
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Artificial Intelligence in Entomology: Global Advances, Applications, and Future Directions in Insect Research and Pest Management
Abstract: Artificial Intelligence (AI) is transforming entomology by enabling scalable, data-driven approaches to insect identification, ecological monitoring, and sustainable pest management. This review synthesizes recent global advances in AI applications across taxonomy, behavioral ecology, predictive modeling, and precision agriculture. Machine learning and deep learning techniques—including convolutional neural networks, acoustic classification models, and ensemble predictive algorithms—have demonstrated high classification accuracies (often exceeding 90% under controlled conditions) and improved early detection of pest …
Published in International Journal of Insects · Vol. 3, Issue 1, 2026 · pp. 29–40 Read article
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New trends in Radio Frequency design and making things smaller
Abstract: Recent improvements in wireless communication, the Internet of Things (IoT), and 5G/6G networks have made people want small, powerful radio frequency (RF) equipment. With an emphasis on how developments in materials engineering, circuit architecture, and packaging technologies are redefining RF system integration, this article offers a thorough evaluation of current developments in RF downsizing. System-on-Chip (SoC), System-in-Package (SiP), and Antenna-in-Package (AiP) ideas, which allow tightly integrated RF front-ends with enhanced …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 2, 2025 · pp. 28–34 Read article
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Literature Review and Discussion of Machine Learning Algorithms for Predicting Chronic Kidney Disease
Abstract: Being one of the most serious and most occurring diseases in our era, chronic kidney disease requires a fast and correct diagnosis. The usage of machine learning in medicine has now grown to such a level that it could be a means of diagnosis. The doctor can be the first one to get the ailment by using machine learning classifier algorithms. This has been the data science sector’s new horizons, …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 34–39 Read article
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Improved Power Transfer Capability and Optimization of Photovoltaic Power Plants
Abstract: Grid integration is the process of linking distributed energy resources, such as small-scale photovoltaic systems, to the electrical grid. Improving the power quality in the integrated grid of small-scale solar plants requires addressing many technological issues in order to create a secondary distribution network. Thus, this review provides a thorough synopsis of the current state of the art in power quality improvement methods for grid integration, with a focus on …
Published in Trends in Electrical Engineering · Vol. 15, Issue 3, 2025 · pp. 12–20 Read article
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How Scientists Look for New Pathogens Before They Spread
Abstract: Emerging infectious illnesses are a persistent danger to global health. They often come from unexpected places, such wildlife reservoirs, changes in the climate, or human activities. Finding new diseases before they create epidemics is one of the biggest problems in modern epidemiology. This article talks about how scientists use genetic monitoring, field sampling, and real-time data processing to find, track, and describe new infectious organisms in a way that works …
Published in International Journal of Pathogens · Vol. 3, Issue 1, 2026 · pp. 11–17 Read article
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Social Capital as a Predicting Indicator to Measure the Psychological Health Impacts of COVID-19 Pandemic on Urban Societies in Pakistan.
Abstract: The COVID-19 pandemic has forced people to adapt to massive changes in their lifestyles; from health to work and how they interact with everyone nearby they know. This study aims to investigate the psychological wellbeing-impacts of COVID-19 on social capital in Pakistan. Social capital means the social and cultural coherence (as a predicting indicator) in the society. This was a survey based study conducted in 5 major cities (Islamabad, Rawalpindi, …
Published in International Journal of Urban Design and Development · Vol. 2, Issue 1, 2024 · pp. 12–21 Read article
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Deep Learning Algorithms for Medical Image Encryption to Ensure Secure Data Transfer
Abstract: Deep learning has significantly impacted various fields, including medical imaging, by offering new ways to encrypt medical images for secure data transfer. This research work examines how deep learning algorithms are used to enhance medical image security during transmission. Given the high sensitivity and privacy requirements of medical data, it’s crucial to maintain its confidentiality. Traditional encryption techniques, while reliable, often struggle with issues like scalability, computational efficiency, and the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 28–36 Read article
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Manufacturing Processes and 3D Printing of Health Diagnostic Tools: Economic Analysis of Open Source Frameworks
Abstract: Health diagnosis tools, for example, the incorporation of 3D printing into their manufacturing, drastically changed medical technology, providing cheap, customizable, fast tools in the field. This transformation has been accelerated by open-source frameworks that decrease dependence upon proprietary manufacturing and increase accessibility to diagnostic tools. Economic benefits of open-source 3D printing include reduced production costs, less dependence on global supply chains, and better equity of access to health care globally. …
Published in Journal of Open Source Developments · Vol. 12, Issue 1, 2025 · pp. 43–46 Read article
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Polymers and others Advance Materials: A State-of-the-Art Review
Abstract: Developing emerging technologies requires pushing the boundaries of material science. Right now, conventional neat polymers simply do not last long enough in the field. They suffer from sudden mechanical failure, struggle with thermal instability, and throwaway disposal methods have created a massive environmental crisis. To tackle these exact issues, this review provides a critical evaluation of two rapidly growing solutions: sustainable bio-composites and self-healing polymer systems. Rather than offering a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 108–119 Read article
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A Study to Assess the Knowledge on First-Aid Management of Burns Among Adults Living in Selected Areas at Honavar, Uttara Kannada with A View to Organize a Demonstration Programme
Abstract: Title: A Study to Evaluate the Awareness of First-Aid Treatment for Burns among Adults Residing in Specific Areas of Honnavar, Uttara Kannada, Aimed at Organizing a Demonstration Program. Aim: To assess the knowledge on first-aid management of burns and conduct a demonstration program on domestic fire accident. Methodology: A one group pre-test only design was adopted. A total of 100 participants who met the inclusion criteria were chosen through a …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 2, Issue 2, 2024 · pp. 1–6 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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GreenDiagnosis: Intelligent Crop Disease Detection Using Deep Learning Algorithm
Abstract: Agriculture in parts of India relies on labour-intensive traditions, maintaining disease-free crops is crucial. Manual methods can be inaccurate, driving farmers towards AI-based solutions. AI offers a proactive approach to address real-time farming challenges. Among these is the invasion of pests, which diminishes crop quality. Combating pest-related diseases poses a challenge, prompting innovation. Effective surveillance and early detection of crop diseases play a pivotal role in ensuring global food security …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
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Response of Mung Bean (Vigna Radiata (L.) R. Wilczek) Varieties to Bradyrhizobium Inoculation at Gimbo District, Southwestern Ethiopia
Abstract: Globally, mung beans are grown in tropical and subtropical climates as an essential pulse crop. However, lack of appropriate nutrient management combined with the best responsive varieties is a major problem in enhancing productivity of mung bean. Thus, this field experiment was conducted in Gimbo district, Southwest Ethiopia, during the 2024–2025 rain-fed cropping season to evaluate the response of mung bean varieties to Bradyrhizobium inoculation. The treatments comprised factorial combinations …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 1, 2026 · pp. 28–37 Read article
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Lesser-Known Metabolites Influencing Ovarian Function, Follicular Development, and Embryo Viability in Dairy Cows
Abstract: The intricate processes of ovarian function, follicular development, and embryo viability in dairy cows are tightly regulated by a complex network of metabolites. While conventional biomarkers, such as steroid hormones, amino acids, and glucose metabolites, have been extensively studied, a growing body of evidence suggests that lesser-known metabolites play pivotal roles in bovine reproductive physiology. Dairy cattle fertility is critical for maintaining optimal milk production and herd sustainability, necessitating deeper …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 15, Issue 3, 2025 · pp. 18–29 Read article