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1045 articles for “U-net”
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Impact of Phosphorus Application Rates on Yield and Yield Components of Common Bean (Phaseolus vulgaris L.) Varieties in Relation to Water Resources at Yabello, Southern Oromia, Ethiopia
Abstract: Common bean is a key legume crop with significant economic importance in Ethiopia, particularly in the southern region of Oromia. One of the primary constraints to common bean productivity in this region is the issue of soil fertility, which is exacerbated by water scarcity. This study was conducted to assess the impact of phosphorus (P) fertilizer rates on common bean growth and yield, as well as to identify sustainable management …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 3, 2024 · pp. 20–31 Read article
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Bird-Tree Associations and Co-occurrence Patterns in Delhi: Implications for Urban Ecological Restoration and Invasive Species Management
Abstract: Urban trees and birds are intertwined indicators of ecological resilience in cities. This study maps citywide bird-tree interactions in Delhi, India, hosting more than 300 avian species. The city was divided into hexagonal grids, and bird-tree data (506 interactions) were collected through field surveys across 131 sites using standardised 1-kilometre transects. Native keystone species like ficus supported the greatest bird diversity, while invasive Prosopis juliflora was widely used for perching …
Published in Research & Reviews : Journal of Ecology · Vol. 16, Issue 2, 2026 Read article
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Design and Development of Automatic Solar Tracker System for Wireless Sensor Network Node
Abstract: Energy Harvesting Technique (EHT) extracts energy from the renewable sources available in environment. Among all, the solar energy harvesting technique extracts maximum harvested power. The need for energy has grown in recent years in commercial, residential, agricultural, and industrial sectors. Non-conventional or renewable energy sources are being examined as an alternative when traditional, conventional energy sources run out. They are devoid of pollution and kind to the environment. Energy is …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 1, 2025 · pp. 10–17 Read article
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Electronic Drones: Technology, Applications, and Future Directions
Abstract: Electronic drones, commonly referred to as Unmanned Aerial Vehicles (UAVs), have transitioned from exclusively military platforms to indispensable tools across commercial, scientific, industrial, and recreational domains. The rapid evolution of electronics, flight control systems, communication networks, onboard sensors, and artificial intelligence has reshaped drone capabilities, enabling high-precision remote sensing, autonomous navigation, swarm behavior, and integration into complex systems like the Internet of Drones (IoD). This paper examines the technological building …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 15–19 Read article
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Utilizing Artificial Intelligence and Remote Sensing to Predict Flooding in Real-Time and Address Climate Resilience Policy in South Asia
Abstract: South Asia, a region characterized by hydro-climatic instability, faces an intensifying risk from devastating flooding, aggravated by human-induced climate change and intricate river basin interactions. Traditional flood prediction systems, based on limited in-situ data and resource-intensive physical models, have serious delays and resolution problems that make it harder to reduce disaster risk. The combined applications of Artificial Intelligence (AI) and high-resolution remote sensing (RS) constitute a paradigm shift in real-time …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 Read article
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Tank Water Quality Analysis Using Machine Learning
Abstract: Tank Water quality is a critical factor for public health, agriculture, as well as industry. Continuous monitoring of tank water quality: temperature, humidity, water level, CO2 concentration, and pH, is vital for safe usage. Using machine learning, real-time data analysis can detect anomalies, predict issues, and optimize water management, ensuring timely responses and improved safety. This intelligent approach enhances decision-making and maintains water quality effectively in various environments.We develop an …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 27–34 Read article
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Emerging Trends in Data Structures for Modern Machine Learning Applications
Abstract: In the realm of machine learning, data structures play a pivotal role in facilitating efficient data manipulation, storage, and retrieval, thereby significantly impacting the performance and scalability of machine learning algorithms. In recent years, the field of machine learning has witnessed the emergence of novel data structures tailored to address scalability and efficiency challenges inherent in handling large-scale and high-dimensional data. This study provides a look at the data preprocessing, …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 1–7 Read article
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Semantic Network Technology and Digital Library
Abstract: In recent years, the volume of information available on the internet has grown rapidly, leading to the need for more effective ways to manage and access high-quality content. Much of this reliable and well-structured information is stored in digital libraries, which serve as centralized hubs for organized knowledge. However, despite their usefulness, managing and navigating these vast collections of data continues to present significant challenges. To address these issues, the …
Published in Current Trends in Information Technology · Vol. 15, Issue 2, 2025 · pp. 13–18 Read article
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Optimizing Glass to Metal Composite Seal Performance: An integrated Approach with Artificial Neural Network, Multiple Regression, and Taguchi
Abstract: Composite materials, particularly glass to metal composites, are critical components in solar receiver tubes, where vacuum leakage can significantly compromise the efficiency of solar plants. This research addresses the technical barriers associated with the development of durable and high-quality glass to metal composite seals. We investigate the principles that can enhance the physical and chemical properties of these composite seals, focusing on the incorporation of TiO2 and MgO nanoparticles into …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 418–435 Read article
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Psychological Determinants of Farmers’ Adoption of Sustainable Practices: A Behavioural Approach to Agricultural Extension
Abstract: Sustainable agriculture has emerged as a global priority to balance productivity with environmental conservation. Yet, adoption of sustainable practices by farmers remains uneven, shaped not only by economic incentives but by underlying psychological and behavioural factors. This review explores the psychological determinants influencing farmers’ willingness to adopt sustainable agricultural practices across traditional and modern contexts. Drawing upon behavioural theories such as the Theory of Planned Behaviour and the Diffusion of …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 101–109 Read article
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AI Hindi Poem Generator
Abstract: The Hindi Poetry Generator project represents a pioneering initiative in the domain of computational creativity, blending machine learning algorithms and natural language processing methodologies to craft poetic expressions in the Hindi language. Rooted in the vast landscape of Hindi literature, this project harnesses the power of deep learning models to generate evocative and culturally significant poetry. At its core, the system relies on neural networks and sophisticated language modeling techniques …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 10–16 Read article
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Enhancing Smart Grid Resilience Through AI-Based Fault Classification
Abstract: Traditional power grids can be developed into smart grids, and they are comprised of the latest information and communication technologies (ICTs), which are based on establishing the relationship between the conventional electricity systems along with the usage of smart meters and distributed generation. This dynamic improves energy efficiency and the integration of renewables. Well, the dynamic and reversible power injection from Distributed Energy Resources (DERs) creates substantial operational problems. These …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article
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IoT Innovations in Power System Monitoring: Reviewing Transmission Line Multiple Fault Detection Systems
Abstract: In this review, it is possible to highlight a new project idea called Transmission Line Multiple Fault Detection System with Internet of Things (IoT). It is a IoT based research that helps in identifying multiple failures on transmission lines leading to fast and correct response. It consist of installing many senors of different types like temperature sensors, current sensors, and vibration sensors on the lines in order to carry out …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 1, 2024 · pp. 20–28 Read article
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Mechanical Strength Prediction of Nano-Silica Concrete Composites Using Machine Learning Techniques
Abstract: Nano-silica, or nanosilica, refers to silicon dioxide nanoparticles, which are a kind of silica (SiO₂) with diameters that often fall below 100 nanometers. This nanomaterial has attracted considerable attention because of its distinctive characteristics and diverse array of uses, notably in augmenting the performance of materials such as concrete. The integration of nanoparticles with cementitious matrix in nano-silica concrete offers a viable approach to improving the mechanical characteristics and longevity …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 963–973 Read article
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Deep Learning Meets IoT: Hybrid Approaches for Botnet Detection
Abstract: Rapid advancement in the Internet of Things (IoT) changed everything, making it possible for seamless interconnectivity of devices and altering data-driven decision processes. This study delves into the intersection of IoT with deep learning approaches and hybrid approaches for managing botnet in IoT systems, especially security, efficiency, and performance optimization. Leveraging deep learning models, for example, CNNs and RNNs, will help the network achieve more intrusion detection and data analysis. …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 1, 2025 · pp. 18–27 Read article
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Cardiovascular Illness Detection and Categorization with Innovative Neural Networks
Abstract: Health-related problems are increasingly prevalent in modern-day societies and are significantly shaped by a multitude of factors encountered in everyday life. Among these, cardiovascular diseases have emerged as one of the primary causes of death on a global scale, posing serious challenges to public health systems. In response to this growing concern, the present study proposes a machine learning-based framework that is not only highly effective but also reliable and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 21–30 Read article
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ML-Enhanced Smart Sensing Framework for IoT- Based Structural Health Monitoring Using Conductive Polymer Composites
Abstract: The growing demand for intelligent structural health monitoring (SHM) in dynamic infrastructures necessitates flexible sensing systems that are not only mechanically robust but also capable of real-time interpretation. Conventional SHM frameworks often rely on brittle sensor configurations and cloud-dependent processing pipelines, which suffer from latency, limited durability, and poor adaptability under variable loading conditions. Despite recent advances in composite materials and machine learning, current approaches lack a unified framework that …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 348–369 Read article
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Enhancing IoT Network Security with Hybrid Deep Learning Classifiers for DDoS Attack Detection
Abstract: The security and operational dependability of Internet of Things (IoT) networks are seriously threatened by the growing susceptibility to Distributed Denial of Service (DDoS) assaults brought about by their rapid expansion. The intricacy and dynamic character of these advanced attacks can provide a challenge to conventional intrusion detection systems. This study presents a novel method for strengthening IoT network security by combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
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Analysis of Power Quality Disturbances in Distribution Systems with Renewable Energy Integration
Abstract: The growing integration of renewable energy sources within the electrical distribution systems has greatly altered the working dynamics of the contemporary power grids. The introduction of intermittent and nonlinear sources (solar photovoltaic and wind energy systems) leads to a wide range of power quality disturbances, however. The current paper includes the in-depth examination of the problem of power quality in the distribution systems with the integration of renewable energy. The …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 Read article
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Early Lung Cancer Prediction using deep Learning
Abstract: Lung cancer is a global killer because it’s often found late. Finding it early is key to treatment and survival so computer assisted diagnostics are essential. This research uses deep learning to spot early stage lung cancer from CT scans. We trained and fine-tuned three convolutional neural networks—ResNet50, Dense Net 201 and EfficientNet-B0—using transfer learning. We preprocessed the lung CT images by resizing, normalizing and augmenting them to enhance the …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 Read article