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1976 articles for “font meta- data” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Integrating Network Pharmacology and Molecular Docking to Investigate Boerhavia diffusa for Pancreatic Cancer Treatment
Abstract: Objective: In this study, network pharmacology was applied to determine the therapeutic effects of the bioactive compounds of Boerhavia diffusa. Network pharmacology can unearth the underlying mechanisms between drugs and the disease targets and aids in the discovery of novel medications for complex conditions such as cancer. Methods: To predict the molecular mechanisms of action of Boerhavia diffusa in the treatment of was screened using the GeneCards database. The Venn …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 1, 2024 · pp. 29–49 Read article
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Integrating Blockchain with IoT: A Survey of Security Techniques and Future Directions
Abstract: Data is a resource that is more crucial than ever for each company that comes to mind. The ability to swiftly and efficiently collect data anywhere is made possible by current breakthroughs and trends such as cloud computing, IoT, data analytics, and others. One of those concerns is the need to strike a balance between privacy and the use of data for security in applications such as IOT, counterterrorism, and …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 25–31 Read article
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Association Rule Mining for Predicting Heart Disease: Challenges and Opportunities
Abstract: The exponential growth of digital healthcare data has spurred innovative applications of data mining techniques in medical research and practice. Among these, association rule mining stands out for its ability to uncover meaningful correlations within diverse datasets, such as electronic health records, imaging data, and genetic information. This paper reviews the application of association rule mining in predicting heart diseases, emphasizing its potential to enhance early detection, risk stratification, and …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 3, 2024 · pp. 29–34 Read article
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Integration of AI and Machine Learning in Smart Environment Monitoring Systems
Abstract: The Internet of Things (IoT) plays an important role in our lives. Many real-time changes in logistics environment monitoring and location tracking can be measured using IoT. It uses a wireless sensor network to monitor important changes in the environment. In this article a comparative review study has been performed in which one side wireless sensor network is integrated with IoT only while on the other side wireless sensor network …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 15, Issue 2, 2024 · pp. 13–19 Read article
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Impact of Fly Ash Pollution on Quality of Agricultural Soils Around Thermal Power Station
Abstract: The coal-fired Khaparkheda Thermal Power Station (KTPS) and its fly ash pond in Nagpur District, Maharashtra, India has been responsible for serious fly ash pollution incidents of agricultural soil. The present study was carried out on the quality of soil samples around the fly ash pond and KTPS. The physicochemical and chemical characteristics of soil samples were observed to be affected due to fly ash pollution. The fertility of soil …
Published in Research & Reviews : Journal of Ecology · Vol. 14, Issue 1, 2025 · pp. 6–17 Read article
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Statistical Models for Predicting Genetic Variability and Disease Susceptibility
Abstract: Differences in genetics are key to understanding why some individuals are more prone to certain diseases than others. Recent advancements in genomic research, combined with statistical modeling techniques, have made significant strides in predicting disease risk based on genetic factors. This review explores the application of statistical models for predicting genetic variability and their role in disease susceptibility. We discuss traditional methods like linear regression and genome-wide association studies (GWAS), …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 30–34 Read article
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A Practical Approach for Privacy Preserving in Cloud Computing Using Fully Homomorphic Encryption Scheme BFV and CKKS
Abstract: Cloud computing is a new type of computing architecture whereby data may be accessed over the Internet along with other services linked to its scalable data centers in the cloud. The risk associated with computing is increased since it provides essential services that are typically provided to any third party, making it more difficult to enable data security, privacy, confidentiality, integrity, and authentication. To reduce security risks, most users choose …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 1, 2025 · pp. 1–8 Read article
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Synthesis and Characterization of a Naphthalene-Derived Schiff Base for Fe³⁺ Sensing Applications
Abstract: The development of chemosensors for metal ions has gained significant attention due to their crucial role in industrial, environmental, and biological applications. Metal ion detection is essential for monitoring environmental pollution, industrial processes, and biological systems where metal homeostasis plays a vital role. In this study, we focus on the synthesis, characterization, and application of a novel naphthalene-based Schiff base ligand, derived from the condensation reaction between 1,8-diaminonaphthalene and 3-nitrobenzaldehyde. …
Published in International Journal of Cheminformatics · Vol. 2, Issue 2, 2024 · pp. 1–8 Read article
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A Study on Security Requirements of IOT
Abstract: In terms of speed, internet technologies have surpassed traditional technologies. Although the Internet's explosive growth has allowed it to reach its full potential, there are several security dangers associated with it. Many consumer-grade IoT devices are not designed with robust authentication protocols, making them easy targets for hackers. To address this, stronger multi-factor authentication (MFA) methods and certificate-based authentication should be implemented to ensure that only legitimate devices gain access …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 1, 2025 · pp. 24–28 Read article
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Comparative Study of AI-Driven Fashion Trend Prediction System Using AI and ML: A Review
Abstract: To overcome the challenges in fashion trend forecasting, researchers have introduced several advanced and data-driven approaches. One such method uses a long short-term memory (LSTM) model combined with an encoder-decoder architecture to extract meaningful fashion content and recognize styles from product images. This model achieves higher accuracy in predicting upcoming fashion trends by incorporating varying price intervals and has shown impressive results when evaluated on the Amazon fashion dataset. Another …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 35–41 Read article
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A Review on Predicting Wear and Friction of PTFE Composites - Fillers to Machine Learning Models
Abstract: Polytetrafluoroethylene (PTFE) composites, a self-lubricating material with low friction, became an indispensable material in engineering applications where load carrying capacity and wear are crucial. The pure PTFE has poor mechanical strength and wear resistance which can be enhanced by the addition of fillers in appropriate volume fraction. The wear performance is dependent on various factors such as fillers, operating parameters, environmental conditions as well as manufacturing attributes. This makes the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 114–128 Read article
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Pathophysiology Reimagined: Integrating Systems Biology and AI for Disease Understanding
Abstract: Pathophysiology, the study of disease mechanisms at molecular, cellular, and systemic levels, has traditionally relied on reductionist approaches that often fail to capture the complex, dynamic, and interconnected nature of biological systems. Diseases such as cancer, neurodegenerative disorders, and infectious diseases arise from intricate interactions among genetic, epigenetic, metabolic, and environmental factors, necessitating integrative, data-driven methodologies for a deeper understanding. Systems biology has emerged as a powerful approach by leveraging …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 63–71 Read article
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Farmer’s Pal
Abstract: Precision agriculture, characterized by data-driven decision-making, has transformed contemporary farming practices. To increase agricultural sustainability and efficiency, this abstract investigates the combination of sensor monitoring, machine learning, and picture processing. A network of sensors continuously collects vital environmental data, including temperature, humidity, rainfall, sunshine, soil moisture, and conductivity, for precision agriculture. By providing real-time insights, these sensors enable farmers to make informed choices about pest control, fertilization, and irrigation. This …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 19–31 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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IoT Based Weather Monitoring System
Abstract: The Internet of Things (IoT)-Based Weather Monitoring System is developed to provide accurate, real- time monitoring of essential environmental parameters, including temperature, humidity, and atmospheric pressure. The system integrates high-precision sensors with a microcontroller, enabling continuous data acquisition from the surrounding environment. Collected data is transmitted wirelessly to a dedicated IoT platform via an internet connection, allowing remote users to access and visualize the information through web or mobile interfaces. …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 3, 2025 · pp. 26–34 Read article
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Progress and Uses of Satellite Remote Sensing
Abstract: Satellite remote sensing has become an important tool for watching, studying, and controlling both natural and man-made systems on Earth. Satellite sensors collect electromagnetic radiation that is reflected or transmitted from the Earth's surface. This data is needed for environmental monitoring, resource management, and hazard assessment. Recent improvements in sensor resolution, data processing techniques, and cloud-based platforms have made remote sensing applications much more accurate and easier to use. The …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 8–19 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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A Comprehensive Study of Natural Language Processing Systems Using Modern Programming Languages: Techniques, Architectures, Experimental Evaluation and Applications
Abstract: Natural language processing is a key field of study within artificial intelligence that focuses on enabling machines to understand and work with human language. This is because there is much digital text data everywhere. Natural Language Processing is what this study is about. It looks at new ways of doing Natural Language Processing. The old ways are like machine learning, and the new ways are like learning. This study compares …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 · pp. 12–23 Read article
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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 26–33 Read article