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50 articles for “memory management”
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Decoding Big Data: A Practical Comparison Between Hadoop and Spark
Abstract: This paper conducts a comprehensive comparison of Apache Hadoop and Apache Spark, two essential frameworks in the big data era. The rapid expansion of data possesses challenges in terms of volume, variety, and velocity, which necessitate advanced processing solutions. Hadoop, utilizing its MapReduce paradigm, provides scalable and fault-tolerant storage, whereas Spark, built upon Hadoop, introduces in-memory processing to increase speed and flexibility. This study includes a detailed examination of their …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 3, 2024 · pp. 15–23 Read article
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A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article
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Optimizing Data Processing Efficiency in Big Data: Advanced MapReduce Algorithm Innovations
Abstract: The exponential growth of big data in recent years has created an urgent need for innovative and efficient processing frameworks capable of managing and analyzing massive and complex datasets. Among these, MapReduce has gained prominence as a powerful tool for distributed data processing due to its simplicity and scalability. However, traditional MapReduce frameworks often encounter significant limitations in terms of efficiency, scalability, and resource optimization, particularly when handling large-scale and …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 1–7 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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Electroconvulsive Therapy in the Management of Schizophrenia: A Systematic Review in Emergency Nursing Practice
Abstract: Electroconvulsive therapy (ECT) is a well-established treatment for various psychiatric disorders, including schizophrenia, particularly in cases where patients are resistant to conventional treatments. Schizophrenia, a chronic and severe psychiatric disorder, often presents with a combination of positive symptoms (such as hallucinations and delusions), negative symptoms (such as social withdrawal and emotional blunting), and cognitive impairments. While antipsychotic medications are the primary treatment, approximately 20–30% of individuals with schizophrenia do not …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 3, Issue 1, 2025 · pp. 43–48 Read article
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IoT-Enabled Monitoring of AC Condensate Water for Quality Assessment and Early Detection of HVAC System Health
Abstract: The shortage of water and expensive reactive maintenance of HVAC are major problems in the modern building management. The paper introduces an Internet of Things (IoT)-enabled air conditioning (AC) condensate to water resource (predictive maintenance) and sustainable water reuse. The nature of our approach defines the quality of the condensate water at the baseline and indicates that it contains low levels of total dissolved solids (TDS) and has almost neutral …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 1, 2026 · pp. 25–35 Read article
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High-Definition Electroencephalography: A New Horizon in Neurological Pathology Research
Abstract: The advent of high-density electroencephalography (HD-EEG) has catalyzed a paradigm shift in the exploration of neurological pathologies. This editorial underscore its transformative potential in elucidating brain dynamics and refining diagnostic approaches for a spectrum of conditions, spanning from epilepsy and dementia to cognitive impairments in preterm infants. Our objective is to optimize the utility of HD-EEG by emphasizing the imperative for methodological homogenization and fostering collaborative endeavors. The remarkable spatial …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 15–21 Read article
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AI Adoption in Medical Libraries: A Study on SDMH’s Use of Ovid Discovery AI and Its Impact on Evidence-Based Medicine
Abstract: The role of Artificial Intelligence (AI) in transforming medical libraries is increasingly significant as these libraries evolve to become intelligent, responsive hubs for knowledge dissemination. This paper explores the adoption of AI tools at Santokba Durlabhji Memorial Hospital (SDMH) Medical Library, focusing on the integration of Ovid Discovery AI, a cutting-edge tool designed to enhance literature search accuracy, summarize content, and provide context-aware recommendations. Using a mixed-methods approach, the study …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 2, 2026 · pp. 1–9 Read article
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Early Life Nutrition as a Determinant of Long-Term Vaccine Immunogenicity in Livestock: Mechanisms, Practical Strategies, and Species-Specific Considerations
Abstract: Early life represents a critical period for immune system development in livestock, during which nutritional exposures can exert long lasting effects on vaccine immunogenicity. Although vaccination is a cornerstone of infectious disease control in food producing animals, marked variability in vaccine induced immune responses is frequently observed under commercial conditions. Growing evidence suggests that this variability is partly driven by differences in early nutritional status, which can influence immune maturation, …
Published in International Journal of Vaccines · Vol. 3, Issue 1, 2026 · pp. 15–26 Read article
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Kisunla (Donanemab): A Novel Breakthrough Illuminating a Path to Better Alzheimer’s Outcomes
Abstract: Background: Alzheimer’s disease (AD) is a progressive neurodegenerative condition marked by cognitive decline, memory loss, and loss of independence. Despite decades of extensive research, disease-modifying treatments have been limited in success. Recent therapeutic advancements have led to the development of monoclonal antibodies targeting amyloid-beta (Aβ) plaques, particularly the pyroglutamate-modified variant, a key pathological hallmark of AD. Objectives: This review aims to explore the therapeutic potential of Donanemab (Kisunla), a novel …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 37–45 Read article