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1932 articles for “Limitation” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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AI, Robotics, and the Future of Waste Management: A Systematic Review of Advanced Collection and Sorting Systems
Abstract: The rapid growth of cities and rise in population have made waste management a major concern that calls for innovative and efficient solutions. Conventional waste collecting techniques are dangerous, time-consuming, and frequently ineffective. The development of automated waste management systems powered by cutting-edge technology like robotics, deep learning, artificial intelligence (AI), and the Internet of Things (IoT) is examined in this study. Vision-based systems, convolutional neural networks (CNN) for garbage …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 1–6 Read article
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Automatic Brake Failure Indication with Auxiliary Braking System
Abstract: Accidents in vehicles often happen due to diverse factors, with brake failure being a significant contributor resulting from inadequate maintenance and product defects. To protect human lives and reduce the risk of accidents, effective monitoring of brake systems is vital in the automotive industry. Vehicle safety encompasses not only the prevention of accidents but also the mitigation of their adverse effects on human health. Today’s cars come with innovative safety …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 1–7 Read article
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Evaluating the Effects of Self-Care Practices on Dermatology Patients at Sharda University Hospital
Abstract: Self-care is the ability of individuals, families and communities to promote their own health, prevent disease, maintain health, and to cope with illness with or without the support of a health or care worker." (WHO, 2020) This study looked into the demographics and self-care activities of patients who visited the Dermatology Department at Sharda Hospital. A descriptive survey design was used, with 50 participants aged 18-45 years selected using convenience …
Published in International Journal of Community Health Nursing And Practices · Vol. 3, Issue 2, 2025 Read article
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Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches
Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 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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Optimizing Chromatographic Techniques for Comprehensive Paraben Analysis to Enhance Safety in Consumer Products
Abstract: Parabens (PBs), such as methylparaben (MePB), ethylparaben (EtPB), propylparaben (PrPB), and butylparaben (BuPB), are widely used as preservatives in pharmaceuticals, food, and personal care products due to their antibacterial properties. However, there are growing worries about their potential to disrupt hormonal functions, which has led to stricter regulations. This study focuses on creating a robust high-performance liquid chromatography (HPLC) method for quickly measuring all four parabens in consumer goods. We …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 228–243 Read article
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Effect of Carbonyl Iron Particle Concentration on The Printability and Stiffness of Magnetorheological Elastomer Filaments
Abstract: Magnetorheological elastomer (MRE) are increasingly valued for their field-responsive mechanical properties, making them ideal for adaptive components in automotive, aerospace, and vibration control systems. However, conventional mould-based fabrication methods limit design flexibility, produce excess material waste, and are unsuitable for complex or customized geometries caused challenges that have hindered broader industrial adoption. Although 3D printing offers a compelling alternative, research on printable MRE filaments remains limited, particularly regarding how carbonyl …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 310–317 Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
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Stacked Generalization-Based Deep Learning Approach for Pneumonia Detection
Abstract: The proposed work focuses on a stacked generalization-based approach for diagnosing pneumonia from chest X-ray images. It utilizes regularization, early stopping, and data augmentation to deal with overfitting. It uses safe level SMOTE to deal with class imbalance and attention-based feature fusion to adaptively weigh features based on their importance. It uses two publicly available datasets (RSNA and Kermany) with ground truth provided by expert radiologists. The proposed work used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 20–31 Read article
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Challenges of Upgrading Local Cattle with Exotic Breeds: Genetic, Environmental, Economic, and Sustainability Trade-offs
Abstract: The practice of upgrading local cattle with exotic breeds has gained popularity as a strategy to enhance milk and meat production. While this approach holds potential for improving productivity, it also presents a range of challenges that need careful consideration. This study examines the genetic, environmental, economic, and sustainability trade-offs associated with upgrading local cattle with exotic breeds. From a genetic perspective, upgrading can result in the dilution of traits …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 2, 2025 · pp. 38–53 Read article
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Development of a Low-Cost Autonomous Robot for Obstacle Avoidance Using Ultrasonic Sensing
Abstract: In the evolving landscape of automation, autonomous mobile robots are becoming critical for performing tasks with minimal human intervention. This project presents the design and development of a cost-effective, small-scale obstacle-avoiding robot using an Arduino microcontroller and an ultrasonic sensor. The robot operates by scanning its surroundings, identifying nearby obstacles, and navigating by altering its path in real time. Through intelligent programming and sensor integration, the system achieves smooth, collision-free …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 1, 2026 · pp. 1–11 Read article
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The Role of Helicobacter pylori in Stomach Cancer Incidence: A Study in Rural Communities in Rajasthan
Abstract: Background: Stomach cancer remains a major global health challenge, with a particularly high burden in developing regions. Helicobacter pylori (H. pylori) infection is a known risk factor for gastric malignancy. In India, especially in rural states like Rajasthan, there is limited data on the prevalence of H. pylori and its association with stomach cancer, despite the high incidence of gastric diseases. Methods: This cross-sectional study was conducted among rural communities …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 45–50 Read article
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Pneumonia Identification Using Explainable Artificial Intelligence
Abstract: Pneumonia, including tuberculosis (TB), remains one of the leading causes of death worldwide, especially in regions where access to healthcare is limited. Early and accurate diagnosis is critical for effective treatment and better patient outcomes, but traditional methods are time-consuming and require specialized expertise. This study explores the use of advanced deep learning models VGG16, VGG19, and ResNet50 to detect pneumonia and TB from chest X-ray images. By leveraging transfer …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 01–11 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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Sustainable Membrane Technologies for Environmental and Industrial Applications: A Review
Abstract: Membrane-based technologies have become indispensable in addressing global environmental and industrial challenges, including water scarcity, pollution control, and energy efficiency. While conventional membranes provide high selectivity and process efficiency, their sustainability is limited by factors such as fouling, high energy consumption, and end-of-life waste management. Recent advances in material science, nanotechnology, and bio-inspired design have led to the emergence of sustainable membranes with improved durability, lower environmental footprint, and broader …
Published in International Journal of Membranes · Vol. 2, Issue 2, 2025 · pp. 7–12 Read article
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Climate Change and Air Pollution Dynamics: Synergistic Effects and Mitigation Strategies
Abstract: Climate change and air pollution are deeply interlinked environmental problems that jointly exacerbate human health, ecosystem integrity, and economic well‑being. As global temperatures rise, shifts in meteorological conditions—such as increased heat, altered precipitation, and more frequent extreme weather events—modify pollutant generation, dispersion, chemical transformation, and removal processes. Meanwhile, many sources of air pollution are also sources of greenhouse gases (GHGs), giving rise to potential co‑benefits or trade‑offs when formulating mitigation …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 38–42 Read article
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How Accurate is AI in Education? A Critical Examination of AI in School Education
Abstract: Artificial Intelligence (AI) is reshaping education by supporting personalized learning, streamlining administrative work, and offering intelligent tutoring systems, especially in K-12 and higher education. This research explores AI’s application in classroom instruction, student assessment, and adaptive learning, with a focus on its accuracy in school-based environments. AI tools like automated grading and intelligent tutors demonstrate strong performance in structured tasks such as multiple-choice assessments and content recommendations. However, they struggle …
Published in Journal of Open Source Developments · Vol. 12, Issue 3, 2025 · pp. 11–17 Read article
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AI in Healthcare: Drug Delivery in Tuberculosis
Abstract: Tuberculosis (TB) , mainly caused by Mycobacterium tuberculosis, remains a major global health burden, accounting for millions of new infections and deaths each year. Although progress has been made in diagnosis and treatment, the growing threat of multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB makes disease control increasingly difficult. Conventional diagnostic approaches such as chest X-rays, sputum smear microscopy, and culture methods continue to play an important role, but they …
Published in Trends in Drug Delivery · Vol. 13, Issue 1, 2026 · pp. 9–17 Read article
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A Study to Assess the Knowledge and Attitude on Artificial Intelligence in Health Care Among Nursing Students at a Selected Nursing College in Kuppam
Abstract: Background: Artificial Intelligence (AI) is rapidly gaining prominence in healthcare, holding the potential to revolutionize patient care and streamline administrative processes. However, the preparedness of future nursing professionals for this technological shift, particularly their knowledge and attitudes towards AI in healthcare, remains a critical yet under-investigated area. This study aimed to assess the knowledge and attitudes of nursing students towards AI in healthcare at a selected nursing college in Kuppam, …
Published in Journal of Nursing Science & Practice · Vol. 16, Issue 1, 2026 · pp. 17–23 Read article
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Offloading Computation to the Cloud
Abstract: Mobile devices are increasingly relied upon for complex and resource-intensive applications such as real-time video processing, augmented reality, and machine learning. However, their limited computational power, storage capacity, and battery life pose significant challenges. Computation offloading to the cloud has emerged as a promising solution to overcome these limitations by transferring demanding tasks from mobile devices to remote cloud servers. This approach enables improved performance, reduced energy consumption, and enhanced …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 2, 2025 · pp. 27–37 Read article