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1090 articles for “and Data Processing”
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Classification and Detection of Brain Tumor using Convolutional Neural Network
Abstract: Tumors are masses created when brain cells multiply uncontrollably. A brain tumor is the medical term for this condition. Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Developing a treatment plan is essential to raising a patient's standard of living. Tumors in different regions of the body are evaluated using a variety of imaging techniques, with MRI pictures being utilized mostly for …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Multiple Disease Prediction Using Machine Learning Algorithms
Abstract: The incorporation of machine learning algorithms into healthcare has transformed disease prediction and diagnosis. This research introduces a method for predicting various diseases using machine learning techniques. A comprehensive dataset, consisting of patient records, medical histories, and key disease-related features, was utilized to build predictive models. Data preprocessing methods, including feature selection and normalization, were implemented to clean and prepare the dataset. Several machine learning algorithms, such as Decision Trees, …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 3, 2024 · pp. 34–38 Read article
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Smart Air Filtration Systems for Cities: A Technological Approach to Reducing Urban Pollution
Abstract: Urban air pollution is considered one of the main ecologically critical issues of the 21st century since it threatens citizens' health through respiratory diseases, pathologies of the cardiovascular system, and even premature death. Regarding an extremely high level of pollution in large cities, it becomes necessary to realize technological solutions which could avoid the negative impact of this phenomenon. Smart air filtration systems have emerged as promising solutions for urban …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 2, Issue 2, 2024 · pp. 27–42 Read article
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Pharmacovigilance and drug safety current trends and challenges
Abstract: Pharmacovigilance and drug safety are critical areas of focus in healthcare, aimed at monitoring the safety and efficacy of pharmaceutical products throughout their lifecycle. This review explores current trends, emerging technologies, and challenges in pharmacovigilance, emphasizing their impact on public health and regulatory practices. With the increasing complexity of global pharmaceutical markets, pharmacovigilance systems are evolving to integrate real-time data analytics, artificial intelligence (AI), and machine learning (ML) to detect …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 12, Issue 1, 2025 · pp. 19–27 Read article
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Artificial Intelligence for Improved Healthcare: A Case Study and Applications
Abstract: Artificial intelligence (AI) in healthcare ushers in a revolutionary period of innovation, but it also brings with it significant ethical dilemmas. This paper explores the complex relationship between AI and healthcare, emphasizing both its useful applications and the moral conundrums that arise. Ethical issues span a wide range, including patient privacy, transparency, accountability, and the unintentional reinforcement of biases in AI algorithms. Privacy concerns take center stage as healthcare providers …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 1–12 Read article
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Light-Dark Cycle Disruption in Hypothalamus Tissue of Mus Musculus Causes Change in the Expression of Gm45928 Gene
Abstract: The majority of organisms on earth display consistent 24-hour rhythms in their physiology and behavior due to circadian biology. Light and dark cycles play a key role in setting our internal body clock, which controls things like our sleep patterns, hormone levels, body temperature, and metabolism. The disruption of the light-dark cycle has significant effects on the molecular and behavioral rhythms of the circadian clock of hypothalamus. Gm45928 is a …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 1, 2025 · pp. 32–46 Read article
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An Overview of Artificially Generated Neural Networks Inside the Brain’s Structure in an Alzheimer’s Disease Patient
Abstract: Alzheimer’s disease produces significant neuronal loss, while the precise mechanisms and timing are yet unknown. Other types of cell death, such necroptosis, parthanatosis, ferroptosis, and cuproptosis, need further investigation. Based on brain images of people with mild cognitive impairment, this study assesses artificial neural networks (ANNs) used to diagnose and predict Alzheimer’s disease (AD). This research was conducted considering growing recognition among researchers and medical professionals regarding the importance of …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 2, 2025 Read article
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Application of Convolutional Neural Networks in Design of Efficient Pipe Flow System
Abstract: Convolutional Neural Networks exhibit remarkable capabilities in flow pattern recognition, pressure drop prediction, leak detection, and system optimization through their ability to process complex spatial and temporal data patterns. The study examines CNN architectures specifically adapted for fluid dynamics applications, including data preprocessing techniques, feature extraction methods, and performance optimization strategies. Key applications include real-time flow monitoring, predictive maintenance, design parameter optimization, and anomaly detection in pipe networks. Comparative analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 1–9 Read article
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Choosing the Right Machine: A Comparative Analysis of Desktops and Laptops
Abstract: This study provides a comparative analysis of desktop and laptop computers, focusing on factors such as performance, portability, cost, and user requirements. Desktops are highlighted as the preferred option for resource-intensive tasks like gaming, video editing, and handling large-scale data because of their powerful processors, efficient cooling mechanisms, and expandability. These systems are well suited for users who prioritize high performance and the ability to upgrade components over time. On …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 41–49 Read article
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An Intelligent Neural Networks Approach for Monitoring of Soilless Urban Farms
Abstract: Urban agriculture is increasingly recognized as a sustainable approach to addressing food security challenges in rapidly growing and densely populated cities. Conventional soil-based farming often faces limitations such as space scarcity, excessive water consumption, and environmental degradation. To overcome these challenges, soilless farming techniques such as hydroponics and aeroponics have gained significant attention due to their efficient utilization of space, reduced water requirements, and potential for year-round crop production. However, …
Published in Journal of Water Resource Engineering and Management · Vol. 12, Issue 3, 2025 · pp. 31–37 Read article
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Digital Frontiers in Life Sciences: The Transformative Role of Computing in Modern Biology
Abstract: The integration of computers in the biological sciences has revolutionized research and experimentation, facilitating advancements in areas such as genomics, bioinformatics, systems biology, and ecological modeling. The ability to process vast amounts of biological data efficiently has transformed how scientists study complex biological systems and phenomena. Computational tools enable the analysis of DNA sequences, protein structures, metabolic pathways, and ecological dynamics, which were previously beyond the reach of traditional laboratory …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 Read article
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AI-Based Machine Learning Web Application Firewall (ML-WAF)
Abstract: This research investigates the use of deep learning techniques for the real-time detection of malicious activities in web traffic and proposes an intelligent, AI-driven Web Application Firewall (WAF) designed to provide automated and adaptive security. The system analyzes diverse components of HTTP requests, including request methods, URLs, headers, cookies, and payload content, to accurately identify and classify malicious behavior. The proposed model targets a wide range of common and critical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Jowar Millet Crop Monitoring and Analysis Robot (JMAR): A Smart Solution for Plant and Soil Health in Jowar Millet Farming
Abstract: Farmers cultivating jowar millet (Sorghum) face significant challenges in maintaining crop health and optimizing yield due to the limitations of traditional plant disease detection and soil health assessment methods. Visual inspection and indigenous knowledge are labour-intensive, time-consuming, and often inaccurate, while soil monitoring requires specialized equipment that is not always affordable or accessible. These issues hinder timely intervention and can lead to crop losses and soil degradation. To address these …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
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The Green Cost of Generative Ai: Environmental Sustainability Implications of Large-Scale Ai Systems
Abstract: Generative Artificial Intelligence (GenAI) has advanced rapidly in scale and complexity, enabling powerful capabilities in automated content creation, multimodal reasoning and real-time decision support across sectors. While these systems offer significant technological and economic benefits, their environmental implications are not fully examined. Large-scale GenAI models rely on high-performance computing infrastructure that consumes substantial energy and resources throughout their lifecycle, raising critical sustainability concerns. This paper offers a sustainability-oriented assessment of …
Published in International Journal of Sustainability · Vol. 3, Issue 1, 2026 · pp. 12–20 Read article
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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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Bloodline: A Efficient Interface for Urgent Blood Availability
Abstract: Blood donation and transfusion have long been critical issues, with blood shortages worldwide leading to many preventable deaths. One of the key challenges contributing to these shortages is the absence of a centralized system for managing blood donations. Traditional methods of blood collection are increasingly outdated in the digital age, highlighting the need for an automated system to streamline donation processes and provide information to those in need. To address …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 2, 2025 · pp. 28–36 Read article
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Machine Learning Assisted Design and Analysis of Polymer Composite Materials for Sustainable Renewable Energy Systems
Abstract: Accurate prediction and optimization of polymer composite properties is of paramount importance in the design of these lightweight, durable, and sustainable materials within renewable energy technologies. This work will provide a holistic machine learning-assisted framework that unites materials informatics with domain-specific features and state-of-the-art ML methodologies in the prediction of the mechanical properties of polymer composites, such as tensile strength. This includes embedding several ensemble models, including Random Forest and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 391–402 Read article
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Time Series Methods in Meteorology: A Review of Predictive Models and Applications
Abstract: The accurate prediction of time series data holds substantial significance in various fields, enabling informed decision-making and resource optimization. In this study, temperature variations over time are predicted using the Autoregressive Integrated Moving Average (ARIMA) model. Reliable temperature projections are more important now than ever because of climate change and its effects. For time series prediction problems, the ARIMA model—which is well-known for its ability to capture temporal dependencies in …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 35–46 Read article
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Machine Learning Based Sentiment Analysis of Student Feedback in Higher Education
Abstract: Educational institutions routinely collect feedback from students to understand their perceptions of academic programs, infrastructure, and campus facilities, to improve the overall quality of the college environment. In current practice, feedback is often gathered using numerical or grade-based rating systems, which tend to oversimplify student opinions and may overlook important details related to their level of satisfaction. In contrast, open-ended textual feedback allows students to clearly express their views, concerns, …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 01–10 Read article
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Understanding of Research Bias in Herbal Medicine: A Comprehensive Review
Abstract: Background: The communication and generation of knowledge are central to research. In herbal medicine, with its deep historical roots, research must be methodologically rigorous and unbiased to validate traditional knowledge in modern contexts. Bias, defined as any tendency preventing objective evaluation of a research question, compromises validity and reliability. Objective: To highlight types of research bias in herbal medicine and discuss strategies for minimization to ensure credible and applicable findings. …
Published in Research & Reviews : Journal of Herbal Science · Vol. 15, Issue 1, 2026 · pp. 31–35 Read article