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564 articles for “drying methods”
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A Comprehensive Review of Deep Compressive Sensing for Efficient IoT Data Management
Abstract: The Internet of Things has revolutionized data-driven ecosystems and offers advanced services, such as live monitoring and automation in various domains: smart cities, healthcare, and industrial automation. However, with the exponential growth of IoT devices, comes a large amount of data generation, which poses considerable problems like network congestion, latency, and energy inefficiency. Compressive sensing (CS), one of the newest signal processing methodologies, has emerged as an enabler to meet …
Published in Trends in Electrical Engineering · Vol. 14, Issue 3, 2024 Read article
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Synthesis, characterizations, and challenges of magnetic Zn x Fe 2-x O 3 nanoparticles
Abstract: Diluted magnetic semiconductors comprising magnetic nanoparticles are a driving force in a variety of applications, including biomedicine, bioelectronics, photocatalytic activities, and nanosensors. However, the functionality of these nanomaterials can be influenced by several factors, such as synthesis route, characterization procedures, source, crystal size, and morphology. In this research, emphasis is devoted to synthesizing and characterizing magnetic nanoparticles. Most importantly, it is focused on biological methods, Co-precipitation methods, hydrothermal Gravity methods, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
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Diabetes Risk Prediction from Survey Data Using Machine Learning Algorithms
Abstract: Diabetes mellitus represents one of the most significant global health challenges, affecting millions worldwide and leading to severe complications if left undiagnosed or poorly managed. Early detection and risk assessment are crucial for preventing the progression of this chronic condition. This research presents a comprehensive machine learning approach for predicting diabetes risk using survey-based health parameters. The study implements and compares four prominent classification algorithms: Logistic Regression, K-Nearest Neighbors (KNN), …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Next-Generation Biodegradable Polymer Composites: Enhancing Mechanical and Thermal Performance through Green Reinforcements
Abstract: Next-generation biodegradable polymer composites, combining compostable matrices such as polylactic acid (PLA), polyhydroxyalkanoates (PHAs) and starch-based polymers with green reinforcements (e.g., nanocellulose, lignin, agricultural residues and other bio-fillers), offer a pragmatic route to reconcile high performance with end-of-life sustainability. This paper examines recent advances in the design, processing and interfacial engineering of such composites to enhance mechanical stiffness, strength, toughness and thermal stability while preserving—or intentionally controlling—biodegradation pathways. Emphasis is …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1780–1794 Read article
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Investigation of High reliable electric vehicles drive with fast charging system
Abstract: Per capita, India has the world's biggest battery electric vehicle market. For the last several years, there has been a lot of discussion about the challenges and prospects of integrating electric vehicles (EV) with an electric grid. A battery model of an EV should have suitable control mechanisms to interact with an electric grid. The growth of and accessibility of fast-charging technology is one of the many technological concerns being …
Published in Trends in Electrical Engineering · Vol. 15, Issue 1, 2025 · pp. 44–50 Read article
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Exploring Envelope Design Through a Biomimetic Approach for Enhanced Thermal Comfort
Abstract: This research explores how biomimicry can transform building envelopes to create comfortable indoor climates, particularly in India’s hot, dry regions. With rising temperatures and dense urbanization, conventional buildings heavily reliant on air conditioning are unsustainable. Biomimicry, inspired by nature’s designs, offers an alternative to enhance adaptability, resilience, and energy efficiency in climate-responsive buildings. The study bridges the gap between conventional envelope design and climate adaptability by examining biomimetic principles for …
Published in International Journal of Architectural Design and Planning · Vol. 3, Issue 2, 2025 · pp. 79–110 Read article
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Codal Validation and Optimization of Gantry Girders Under Variable Wheelbase and Impact Loads: A Review of Analytical, Numerical, and Codal Approaches
Abstract: Gantry girders serve as critical structural elements in industrial facilities such as steel plants, workshops, and heavy manufacturing units, where electric overhead traveling (EOT) cranes operate. The design of these girders is governed by stringent codal provisions to ensure safety under bending, shear, and deflection. However, discrepancies between codal predictions, analytical formulations, and finite element analysis (FEA) results, particularly under variable wheelbase and dynamic impact loads, have been widely reported. …
Published in Journal of Offshore Structure and Technology · Vol. 12, Issue 3, 2025 · pp. 23–29 Read article
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Swarm-Enabled AI for Smart Mobility and Sustainable Transport
Abstract: The significant issues facing the modern urban infrastructure are the management of road traffic problems, such as severe traffic congestion, the detection of unsafe driving behavior, and road safety. The traditional ground-based surveillance systems will be helpful, but they will reach their limits in large and dynamic environments. It is because of predetermined perspectives, blindness, and the inability to scale. To designate these problems, the present study proposes a traffic …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 1, 2026 · pp. 33–38 Read article
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Unveiling the Role of Lead Molecules in CADD: A Systematic Review
Abstract: The word "medicate plan" alludes to the objective creation of modern drugs. Arbitrary screening of engineered compounds, engineered of organically dynamic compounds based on actually happening drugs, amalgamation of basic analogs of actually happening lead particles, and usage of the bioisosteric hypothesis are a few of the strategies that have been utilized. As a result, the most recent drift in medicate plan is to either completely enhance a lead or …
Published in International Journal of Membranes · Vol. 1, Issue 1, 2024 · pp. 37–43 Read article
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Harnessing AI and NLP to Transform Pharma Education Personalization, Learning, and Skill Development
Abstract: Particularly with NLP technologies, it is revolutionizing pharmaceutical education, enhancing human creativity, personalizing learning, and improving student outcomes. AI models like those from Open AI’s Chat GPT are increasingly integrated into educational practices that offer a solution to issues, such as teacher shortages, resource limitations, and the inefficient use of traditional teaching methods. This paper explores the diverse ways through which AI and NLP technologies are transforming pharma education within …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 1, 2025 · pp. 7–13 Read article
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Recent Advances in Quality Control and Quality Assurance: Enhancing Pharmaceutical Product Integrity and Compliance
Abstract: The pharmaceutical industry is undergoing a paradigm shift driven by stringent regulatory expectations and the demand for high-quality, safe, and efficacious drug products. Quality Control (QC) and Quality Assurance (QA) serve as the two foundational pillars that ensure pharmaceutical integrity from raw material acquisition through to product release. Traditional QC and QA practices, while effective, have been challenged by complex formulations, biologics, and personalized medicine, requiring innovative methodologies and technologies. …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 54–62 Read article
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India’s Traditional Medicine Trade (2015–2024): Trends, Regulatory Landscape, and Policy Directions for Sustainable Growth
Abstract: India is a major global supplier of traditional medicine products – including Ayurvedic, Unani, Siddha, homeopathic, and other herbal and plant-based formulations – yet exports continue to face challenges arising from regulatory divergence, heterogeneous quality-control requirements across markets, and raw-material supply constraints linked to biodiversity pressure and fragmented value chains. This paper systematically analyzes India’s import-export patterns for traditional medicine between 2015 and 2024, maps the regulatory landscape (DGFT, Drugs, …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 13, Issue 1, 2026 · pp. 13–18 Read article
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Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 Read article
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Emerging Trends in Civil Engineering: Sustainability and Digital Transformation
Abstract: Civil engineering has long played a pivotal role in shaping society’s infrastructure, focusing traditionally on construction, design, and the structural integrity of buildings, roads, and bridges. However, recent years have witnessed a profound transformation in the field, driven by the urgent need for sustainable practices and the rapid evolution of technology. This paper provides an in-depth analysis of the latest trends that are redefining civil engineering, with a particular emphasis …
Published in Recent Trends in Civil Engineering & Technology · Vol. 14, Issue 3, 2024 · pp. 8–11 Read article
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Advancements in Humanoid Robot Locomotion: A Review of Control Strategies and Kinematic Models
Abstract: Humanoid robot locomotion has significantly improved over the past few decades, driven by improvements in control strategies and kinematic models. Researchers aim to develop robots that can walk, run, and navigate complex terrains with efficiency and stability. This review explores recent developments in humanoid locomotion, highlighting control strategies such as model predictive control, reinforcement learning, and central pattern generators. Additionally, it examines kinematic models, including inverted pendulum models and zero …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article
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The Impact of Geographical Indications on Sustainable Rural Development: Comprehensive Economic and Cultural Insights from Wayanad, Kerala
Abstract: Geographical Indications (GIs) play a vital role in fostering sustainable rural development by linking unique local products to their geographic origins. This study explores the impact of GIs on economic growth, cultural preservation, and environmental sustainability in Wayanad, Kerala. Drawing from extensive secondary data and detailed case studies including Wayanad Coffee, Jeerakasala Rice, and traditional handicrafts, the research highlights how GI certification enhances market value, improves income levels, and preserves …
Published in International Journal of Rural and Regional Development · Vol. 3, Issue 2, 2025 · pp. 18–29 Read article
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IoT Grass Cutting Robot
Abstract: The demand for efficient and sustainable lawn care solutions has escalated with the increasing urbanization and the need for environmentally friendly practices. In response to this, our group embarked on the development of an innovative IoT-enabled grass cutting robot. This project aims to address the limitations of traditional lawn mowing methods by integrating modern technology to automate and optimize the maintenance process. The proposed grass cutting robot leverages Internet of …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 1, 2025 · pp. 41–52 Read article
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Exploring Emerging Water Disinfection Technologies: A focus on Hydrodynamic Cavitation
Abstract: Availability of clean drinking water is an ongoing global demand. Contaminated water sources, inappropriate waste disposal, and inadequate hygiene procedures exacerbate it. These elements support the growth of pathogenic microbes like bacteria, viruses, and parasites, which cause a variety of diseases that are transmitted by water. Disinfection plays a vital role in water treatment processes by eliminating these pathogens and ensuring public health safety. Commonly used methods like Chlorination, Ozonation, …
Published in Journal of Water Pollution & Purification Research · Vol. 11, Issue 1, 2024 · pp. 44–53 Read article
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Review on Computer-Aided Drug Design in RAS Inhibitor Discovery
Abstract: This review explores the utilization of computer-aided drug design (CADD) methodologies in the discovery of inhibitors targeting the RAS pathway, a pivotal signaling cascade implicated in various cancers. Through an extensive examination of computational tools, methodologies, challenges, and recent advancements, this review aims to provide insights into the role of CADD in accelerating RAS inhibitor discovery. The discovery of effective inhibitors targeting the RAS pathway is of paramount importance in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 11, Issue 3, 2024 · pp. 7–14 Read article
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Machine Learning Pipelines: A Survey on Automation, Scalability, and Deployment Strategies
Abstract: Machine learning (ML) has become a critical enabler of intelligent applications across domains, requiring robust, efficient, and scalable deployment workflows. This review paper provides an in-depth overview of machine learning pipelines, emphasizing three key dimensions: automation, scalability, and deployment methodologies. It begins by exploring automation techniques that reduce manual effort in data ingestion, preprocessing, model selection, and hyperparameter tuning. Tools such as AutoML, TFX, and workflow orchestration platforms are examined …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 17–28 Read article