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502 articles for “Ear Identification”
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Continuous Commissioning Techniques for Ground Source Heat Pumps: Review
Abstract: This study offers a model-based continuous commissioning methodology to find control-related performance gaps in HVAC systems with ground-source heat pumps. Traditional continuous commissioning is still helpful in finding energy performance gaps, even if MBCCx employs a system model as a reference to find operational inefficiencies and control issues arising from subsystem integration. A calibrated physics-based model that depicts the system performance as intended during the design phase forms the basis …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 3, 2025 · pp. 22–36 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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Wind and Earthquake Mitigation: The Impact of Dampers on Tall Structures
Abstract: This paper provides an in-depth examination of the effects of both earthquake and wind loading on high-rise buildings situated across various terrain categories and seismic zones. The research underscores the critical importance of accounting for lateral loads in the design of reinforced concrete structures, as this consideration is essential for maintaining structural stability and ensuring the safety of occupants. The study focuses on identifying the critical design loads for multistory …
Published in Journal of Structural Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 75–83 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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Role of Artificial Intelligence in Transforming Personalized Learning in Education
Abstract: Artificial Intelligence (AI) is revolutionizing personalized education by tailoring learning experiences to meet each student's unique needs. Through advanced algorithms, AI can adapt educational content to align with individual learning speeds, preferences, and styles. Technologies such as adaptive learning systems, smart tutoring tools, and AI-powered assessments offer instant feedback and assist teachers in quickly identifying areas where students may be struggling. Additionally, predictive analytics help anticipate student outcomes, enabling early …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 3, 2025 · pp. 27–32 Read article
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Faults Detection Techniques of Three Phase Induction Motor: A Review
Abstract: Induction motors are the most commonly used machines in industries. It is very robust, inexpensive and easy to maintain. Induction motors appear to various faults during their operation. Accurate fault identification is the prime industrial need to reduce breakdown, maintenance and revenue losses. Therefore, an early fault detection is needed for the protection of the motor against electrical and mechanical failures for continuing their operation safely. The main perspective of …
Published in Journal of Control & Instrumentation · Vol. 9, Issue 1, 2018 · pp. 45–49 Read article
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Formulation Challenges in Long-acting Injectable Small Molecules: Emerging Strategies and Perspectives
Abstract: Long-acting injectable (LAI) formulations represent a transformative approach in pharmacotherapy, particularly for conditions demanding sustained drug exposure over weeks to months. Although biologics have dominated this space historically, the adaptation of LAI technology to small molecules presents a distinct and complex set of challenges rooted in physicochemical properties, manufacturing scalability, and regulatory expectations. This review systematically addresses the principal formulation barriers encountered in developing LAI small-molecule products, including aqueous solubility …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 13, Issue 2, 2026 · pp. 15–26 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Autonomous Drones for Search and Rescue Opera-tions: State of the Art and Future Prospects
Abstract: Autonomous drones have significantly transformed search and rescue (SAR) operations by improving the speed, precision, and overall effectiveness with which rescuers are able to locate and provide assistance to individuals in need. By leveraging state-of-the-art technologies such as computer vision, artificial intelligence (AI), machine learning, and advanced navigation systems, drones have proven invaluable in carrying out complex rescue missions. These technologies enable drones to navigate hazardous environments autonomously, even in …
Published in International Journal on Drones · Vol. 1, Issue 2, 2025 · pp. 9–13 Read article
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GreenDiagnosis: Intelligent Crop Disease Detection Using Deep Learning Algorithm
Abstract: Agriculture in parts of India relies on labour-intensive traditions, maintaining disease-free crops is crucial. Manual methods can be inaccurate, driving farmers towards AI-based solutions. AI offers a proactive approach to address real-time farming challenges. Among these is the invasion of pests, which diminishes crop quality. Combating pest-related diseases poses a challenge, prompting innovation. Effective surveillance and early detection of crop diseases play a pivotal role in ensuring global food security …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
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Early Disease Detection Using Artificial Intelligence
Abstract: Growth in artificial intelligence and machine learning now make it possible for the healthcare sector to be totally transformed by a new chapter, particularly in the era of medical image analysis. This study focuses on harnessing these advancements to develop a sophisticated model for early disease detection across diverse medical domains, majorly in skin disease. By integrating diverse datasets and leveraging advanced algorithms, our methodology aims to identify subtle disease …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 11–19 Read article
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Nanoparticle-Based Early Diagnostic Tools for Tuberculosis and Malaria in Rural India
Abstract: Malaria and Tuberculosis continue to be two major public health challenges in rural India. The interplay between an inefficient health care system, late diagnosis, and under-identification of cases contributes to the high morbidity and mortality associated with TB and Malaria. Conventional methods, such as sputum microscopy for TB, microscopy and rapid diagnostic tests (RDTs) for malaria, have a higher benchmark of sensitivity that requires a certain amount of time, skilled …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 45–51 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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Leveraging Feature Selection Algorithms for Early Detection of Type-2 Diabetes
Abstract: Numerous feature selection algorithms have been proposed in the past to solve the curse of dimensionality problem. The choice of apt feature selection algorithm is still a fundamental area of research. Feature selection is a process of identifying and removing irrelevant features and retaining only the highest contributing feature set. Feature selection algorithms are primarily used in applications like healthcare where the classification accuracy needs to be high. This study …
Published in Journal of Computer Technology & Applications · Vol. 11, Issue 1, 2020 · pp. 13–20 Read article
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A Comparative Machine Learning Framework for Early Prediction of Liver Cancer Using Clinical Attributes
Abstract: One of the main causes of cancer-related death globally is liver cancer, and improving patient outcomes depends heavily on early detection. However, low contrast, noise, organ similarity, and tumor shape and size variability make it difficult to accurately identify and segment liver tumors from medical imaging. Automated liver cancer diagnosis, segmentation, and prognosis have been greatly improved by recent developments in artificial intelligence (AI), especially deep learning. This work presents …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 · pp. 39–47 Read article
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UNDERGROUND CABLE FAULT DETECTION CAR
Abstract: Abstract:-Underground cables along with additional buried assistance can be identified and examinedusing an apparatus known as a cable detector. This is carried out by passing a signal into the earth andthen receiving it back through an antenna. Utilising the received signal endurance, the exact positionand depth of the underground question are found. In doing mining and construction work, this helpsprevent unintended injuries. There are numerous different types of underground cable …
Published in Trends in Mechanical Engineering & Technology · Vol. 13, Issue 1, 2023 · pp. 17–21 Read article
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Non -Invasive Ways to Detect Cancer
Abstract: Cancer is a diverse group of diseases characterized by uncontrolled cell growth and division, affecting millions worldwide and being a leading cause of death. The disease typically involves genetic alterations that disrupt the normal balance of cell growth, leading to the formation of tumors. Tumors can be benign, posing no threat as they do not spread, or malignant, capable of invading nearby tissues and metastasizing. There are more than 100 …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 2, 2024 · pp. 59–67 Read article
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Deep Learning for Earth Observation Using Satellite Imagery: A Comprehensive Review
Abstract: Earth observation (EO) satellites provide continuous, large-scale information about the Earth's land, oceans, atmosphere, vegetation, infrastructure, and environmental conditions. The rapid growth of multispectral, hyperspectral, synthetic aperture radar (SAR), thermal, and high- resolution satellite missions has generated large volumes of heterogeneous spatial and temporal data. Conventional image-processing and machine-learning techniques often require manually designed features and may have difficulty representing the complex spatial, spectral, temporal, and multimodal characteristics of satellite …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 2, 2026 Read article
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Transformative Breakthroughs: Revolutionizing Potato Disease Detection Through Machine Learning
Abstract: Advancements in agricultural technology and the integration of artificial intelligence for diagnosing plant and leaf diseases are crucial for sustainable agricultural development. Conditions like early blight and late blight exert a notable influence on both the quality and quantity of potato harvests. Identifying these leaf diseases manually demands significant labor and a considerable level of expertise. Therefore, efficient, and automated methods for disease detection are essential to improve potato production. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 54–62 Read article
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A Review on Advances in Personalized Medicine: from Genomics to Clinical Applications
Abstract: Personalised medicine, also known as precision medicine, is a revolutionary approach to healthcare that customises medical interventions and treatments for individual patients according to their distinct genetic, environmental, and lifestyle properties. The basic pillar of personalised medicine is genomics, and the area has seen an explosion of genetic information with the advent of high-throughput sequencing tools. Genomic data now provide unprecedented insights into the underlying genetic variations, mutations, and genetic …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 10, Issue 2, 2023 · pp. 13–17 Read article