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712 articles for “data patterns”
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Big Data in Chemistry: Problems and Answers
Abstract: The rapid growth of experimental and computational chemistry data, researchers now have access to vast datasets, presenting both significant opportunities and challenges. This paper explores the primary challenges associated with managing, processing, and utilizing big data in chemistry, including data heterogeneity, integration across various scales and systems, lack of standardized formats, and the need for advanced tools for data analysis. Additionally, the paper discusses the ethical concerns of data ownership, …
Published in International Journal of Cheminformatics · Vol. 2, Issue 1, 2024 · pp. 9–14 Read article
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Effective Implementation of Apriori Algorithm to Develop a Suggestion System Based on Sales History Using Hadoop Environment
Abstract: AbstractThe need for comprehensive support system to analyze and predict the nature of the dynamic market based on the previous records is very vital in competent industries today. The data mining is a process of extracting implicit, previously unknown and potentially useful information from data. Mining is search for relationships and global patterns that exist in the large databases but that are hidden among vast amount of data. Since the …
Published in Journal of Advanced Database Management & Systems · Vol. 3, Issue 3, 2016 · pp. 8–16 Read article
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Comparative Study of the Effects of Forced Use and Functional Retraining in the Improvement of Gait Pattern in Chronic Stroke Patients
Abstract: Stroke is a complex and devastating disease. Despite treatment advances, stroke remains a leading cause of morbidity and mortality. About 29% of stroke patients die within one year whereas 20% of these will die within three months. Prevalence rate for hemiplagia in south India was reported to be 56.9–100,000 as compared to 150–186 per 1,00,000 population for the USA and Europe.Stroke is one of the main causes of death and …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 8, Issue 1, 2019 · pp. 4–9 Read article
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The Influence of Data Analytics on Sports Performance
Abstract: Data analytics has drastically changed how we evaluate, improve, and maintain athletic performance. Coaches used to use subjective observations as well as only limited numbers of statistics to consider player performance; however, tracking technology is now advancing at a fast pace. There are now very large amounts of real-time data available on athletes in regards to speed, movement patterns, fatigue, efficiency, etc. This enables all teams to more accurately make …
Published in Recent Trends in Sports · Vol. 3, Issue 1, 2026 · pp. 15–21 Read article
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AI-Driven Precision Nutrition: Advancing Personalized Dietary Systems for Public Health Equity in Resource-Constrained Environments
Abstract: The dual burden of malnutrition and diet-related non-communicable diseases (NCDs) represents a growing global public health challenge, particularly in low- and middle-income countries. Traditional dietary guidelines are largely population-based and fail to account for individual variability in genetics, metabolism, lifestyle, and environmental exposure. This limitation has led to the emergence of precision nutrition, an evolving field that integrates biological data and computational intelligence to deliver personalized dietary recommendations. This paper …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Detection of Breast Cancer with Python
Abstract: Global cancer data confirms more than 2 million women diagnosed with breast cancer each year reflecting majority of new cancer cases and related deaths, making it significant public health concern. But fortunately, it is also the curable cancer in its early stage. Early diagnosis of breast cancer with timely and effective treatment services improves the prognosis and survival of patients. During classifying tumors, there are significant chances of error and …
Published in Research & Reviews : Journal of Statistics · Vol. 9, Issue 3, 2020 · pp. 5–22 Read article
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The Review on Big Data Sharding and Replication
Abstract: AbstractSharding is a partitioning pattern that places each partition in potentially separate servers; potentially all over the world. A shard is managed by a single server. Data replication is the process of storing data in more than one site or node. It is useful in improving the availability of data. It is simply copying data from a database from one server to another server so that all the users can …
Published in Journal of Advanced Database Management & Systems · Vol. 7, Issue 3, 2020 · pp. 1–10 Read article
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Examining Research Patterns and Concepts in Relation to Frameworks for Sustainable Supply Chain Management (SSCM)
Abstract: Structures abound in writing about Sustainable Supply Chain Management (SSCM). Nevertheless, no effort has been made to date to identify the anomalies in the systems that are in place now and the associated research trends. This research is motivated primarily by a survey of SSCM structures and feature abnormalities. The analysis also promotes new applications and aids in the analysis of SSCM structure constructions and exploration patterns. Using the Scopus …
Published in International Journal of Industrial and Product Design Engineering · Vol. 1, Issue 2, 2023 · pp. 26–41 Read article
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Passenger car fuel economy: Insights from big data analytics
Abstract: The increasing availability of real-world vehicle telematics through On-Board Diagnostics II (OBD-II) systems has enabled data-driven evaluation of passenger car fuel economy beyond conventional laboratory-based test cycles. While standardized certification procedures ensure repeatability, they often fail to capture the influence of real-world traffic conditions, driver behaviour, and transient vehicle operation. This study presents a structured Big Data Analytics (BDA) approach for analysing high-frequency OBD-II data collected from a gasoline passenger …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 9–21 Read article
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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A Transaction Pattern Generation Tool (TPGT) for Prediction of Online Financial Transactions
Abstract: ABSTRACTThe Internet all over the world is growing rapidly. It has given rise to new opportunities in every field we can think of – be it entertainment, business, sports or education. There are two sides to a coin. Internet also has its own disadvantages. One of the major disadvantages is cyber crime – illegal activity committed on the Internet. The Internet, along with its disadvantages, has also exposed us to …
Published in Journal of Computer Technology & Applications · Vol. 3, Issue 3, 2012 · pp. 1–12 Read article
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Revolutionizing Agriculture: Integrating IoT, Machine Learning, and Image Processing for Smart Farming
Abstract: Precision agriculture, characterized by data-driven decision-making, has revolutionized modern farming practices. This abstract explores the integration of sensor monitoring, machine learning, and image processing to enhance agricultural efficiency and sustainability. In precision agriculture, a network of sensors continually collects vital environmental data, including temperature, humidity, rainfall, sunlight, soil moisture, and conductivity. The real-time data supplied by these sensors empowers farmers to make knowledgeable choices concerning irrigation, fertilization, and pest management. …
Published in Journal of Communication Engineering & Systems · Vol. 13, Issue 2, 2023 · pp. 28–45 Read article
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Litterfall Dynamics in different Forest Types of Kumaun Himalaya
Abstract: Litterfall and forest floor data was collected seasonally from 11 different forest types including degraded forests and 3 plantations in Kumaun Himalaya. Litterfall in different forest types varied from 1.25 t/ha for Degraded sal forest to 6.97 t/ha for High altitude oak forest. Among plantations poplar plantation showed highest litter fall (7.24 t ha-1). Most of the forest types were observed with maximum litterfall during summer season. Temperate Conifer forest …
Published in Research & Reviews : Journal of Ecology · Vol. 9, Issue 1, 2020 · pp. 23–30 Read article
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A Study on the Role of Artificial Intelligence in Indian Higher Education System
Abstract: In the present era, Artificial Intelligence (AI) has been transforming learning, teaching, and engaging, by making them more personalized and efficient in every field. In Indian Higher Education system, the application of Artificial Intelligence (AI) technology is improving learning techniques, by natural language processing, machine leaning etc. by students for analyzing data, using algorithms, discovering patterns and making the predictions for outcomes; and instructors may make lessons for each student …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 08–12 Read article
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Implementation of K-Means clustering algorithm with technical indicators to identify Profitable stocks
Abstract: In the ever-changing world of stock market trading, accurately predicting price movements is key to maximizing profits. Technical analysis, which looks at past price data to predict future trends, provides valuable insights for investors. This paper delves into using machine learning methods, particularly the K-Means clustering algorithm, along with moving average data, to categorize daily trading patterns. By breaking down the market into clusters and examining the main patterns within …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 8–14 Read article
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The Role of Artificial Intelligence in Mental Health: Applications in Neurodegenerative Disorders
Abstract: Artificial intelligence (AI) has significantly changed many aspects of medical care, particularly the early evaluation, therapy, and management of neurodegenerative illnesses like Alzheimer's, disease, Parkinson's diseases, and Huntington's diseases. The current research explores the application of AI in mental health with respect to neurological disorders, especially advancements in cognitive examination, neuroimaging analysis, predictive modeling, and customized therapy modalities. Artificial intelligence (AI) systems have shown enormous potential in detecting minute biomarkers …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 15, Issue 3, 2025 · pp. 34–40 Read article
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A Comprehensive Review on Inclusive Education: Critical Approach to Supporting Children with Autism
Abstract: A developmental illness that affects people to varied degrees over a range, autism spectrum disorder (ASD) is defined by difficulty with social interaction, communication, and repetitive activities. This study investigates useful methods for integrating ASD children into regular educational settings. The aim of inclusive education is to integrate students with autism spectrum disorder (ASD) into mainstream classroom environments. The review paper employed a systematic literature review approach, together with comparative …
Published in International Journal of Children · Vol. 1, Issue 2, 2024 · pp. 24–30 Read article
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IoT Sensors to Monitor Pipeline Pressure and Flow Rate Combined with ML-Algorithms to Detect Leakages
Abstract: In the field of fluid mechanics, pipelines are the lifeblood of industries, transporting everything from natural gas and oil to water and chemicals. Maintaining their integrity is paramount for safety, economic efficiency, and environmental protection. Traditional leak detection methods explained in fluid mechanics can be slow, expensive, and sometimes fail to identify small leaks early enough to prevent significant damage. However, the convergence of Internet of Things (IoT) and Machine …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 40–48 Read article
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A study in Leveraging Deep Learning and IoT Arrays for Dynamic, Hyper-Local Atmospheric Intelligence
Abstract: The critical demand for high-resolution, actionable atmospheric data is challenged by the high cost and sparse coverage of traditional regulatory monitoring stations. This paper explores the synergistic paradigm shift enabled by integrating low-cost, dense Internet of Things (IoT) sensor arrays with advanced Artificial Intelligence (AI) methodologies, specifically Deep Learning (DL) models. We address the primary limitations of low-cost sensors—inherent bias, sensitivity to environmental drift (temperature/humidity), and calibration inconsistency—by utilizing AI …
Published in International Journal of Atmosphere · Vol. 2, Issue 2, 2025 · pp. 50–62 Read article
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Diabetes Risk & Al Nutrition Assistant
Abstract: The rising prevalence of diabetes mellitus has emerged as a major global health challenge. Early identification of individuals at risk, combined with personalized lifestyle-based interventions, can significantly reduce future complications. This study presents an AI-driven Nutrition Assistant integrated with a Diabetes Risk Prediction model. The system uses a machine learning classification approach to estimate the likelihood of diabetes based on clinical and nutritional factors, including body mass index, glucose levels, …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 31–38 Read article