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57 articles for “training-only normalization”
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Effectiveness of Different Proprioceptive Mat, Balance Board and Resistance Band Exercise Training Programme to Prevent Ankle Sprain in Athletes
Abstract: Ankle sprain is the injury to one or more ligament in the ankle. It represents one of the most common injuries associated with sport and activity, therefore studies into how to best prevent this condition from occurring are recognised as essential. The ankle movements are restricted due to ankle sprain. This study intended the effectiveness of different proprioceptive Mat, Balance Board and Resistance Band exercise to prevent the recurrent ankle …
Published in Research and Reviews: A Journal of Health Professions · Vol. 4, Issue 3, 2014 · pp. 24–31 Read article
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The Effectiveness of Different Proprioceptive Mat, Balance Board and Resistance Band Exercise Training Programme to Prevent Ankle Sprain in Athletes
Abstract: Ankle sprain is the injury to one or more ligament in the ankle. It represents one of the most common injuries associated with sport and activity, therefore studies into how to best prevent this condition from occurring are recognised as essential. Due to ankle sprain the ankle movements are restricted. This study intended the effectiveness of different proprioceptive mat, balance board and resistance band exercise to prevent the recurrent ankle …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 4, Issue 3, 2014 · pp. 19–25 Read article
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A IoT-Enabled Predictive Intelligence for Real-Time Failure and Damage Evolution Monitoring of Polymer Composites
Abstract: Damage assessment of carbon-fibre-reinforced polymer composites is still challenging since the damage occurs as a combination of matrix cracking, interfacial debonding, delamination and fibre fracture. The present work proposes a framework for predictive-intelligence based on IoT for multiaxial fatigue and compression-after-impact (CAI) CFRP experiments, employing publicly available acoustic-emission (AE) datasets. A causal CNN–GRU attention model is developed by integrating time-domain, spectral, wavelet, loading-history and trend features to estimate the damage …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Alzheimer’s Disease Classification Based on Transfer Learning of New-CNN Model
Abstract: The long-term, irreversible brain disorder “Alzheimer’s disease (AD)” currently has no known cure. Nonetheless, current medications may impede their advancement. Globally, those over 65 are the primary population affected by Alzheimer’s disease. Accurate detection of this condition requires early diagnosis. Because there are so many people who come with an ailment, manual diagnosis by health specialists is laborious and prone to error. Early detection of AD is a difficult undertaking …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 16–23 Read article
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Capacity Building Initiatives for Health Workforce Development in Gujarat, India
Abstract: Human resources are critical component of an efficient and effective health care system. In many developing countries including India, there has been a long-term neglect in the planning and implementation of capacity building efforts for the public health workforce. Recently several states in India have launched variety of initiatives to address this challenge. Efforts for manpower development in Gujarat were initiated in 2000. Present manuscript attempts to document the initiatives …
Published in Research and Reviews: A Journal of Health Professions · Vol. 1, Issue 1-3, 2011 · pp. 9–20 Read article
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An Abnormal Expression Detection System (AEDS) Using Deep Learning Algorithms
Abstract: In the last decade, many deep learning algorithms have achieved remarkable success and gained popularity in various computer vision tasks, including object detection, image recognition, and segmentation. This AEDS (Abnormal Expression Detection System)leverages the power of deep learning algorithms to detect abnormal facial expressions in real-time automatically. AEDS proposed two important models; those are Deep CNN and RNN. CNN is responsible for learning discriminative features from facial images and capturing …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 72–79 Read article
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U-Net Based Approach for Automated Brain Tumor Classification
Abstract: Brain tumor detection and identification play vital roles in diagnostic procedures in the field of medicine, with the conventional analysis of MRI images requiring a lot of time and also subject to variability. The proposed study involves the use of a CNN-U-Net based approach for brain tumor detection and identification automatically. The study uses a database of 3,064 contrast-enhanced T1-weighted MRI images from 233 patients with the tumors of meningioma, …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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Retinal Disease Detection Using Deep CNN
Abstract: Age-related macular degeneration, glaucoma, and diabetic retinopathy are the three main causes of blindness in the globe. To avoid visual loss, early identification and treatment of these disorders are essential. The goal of this research is to create an automated method for detecting retinal diseases by analyzing retinal fundus pictures with machine learning techniques. Python and the Tkinter package for the graphical user interface are used in the construction of …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 46–50 Read article
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Early Lung Cancer Prediction using deep Learning
Abstract: Lung cancer is a global killer because it’s often found late. Finding it early is key to treatment and survival so computer assisted diagnostics are essential. This research uses deep learning to spot early stage lung cancer from CT scans. We trained and fine-tuned three convolutional neural networks—ResNet50, Dense Net 201 and EfficientNet-B0—using transfer learning. We preprocessed the lung CT images by resizing, normalizing and augmenting them to enhance the …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 Read article
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A Study of DCGAN-Based Generative Models for Anime Character Face Generation
Abstract: Artificial intelligence, or AI, has in recent years moved from simple rule-based systems to models that are now fully capable of creative content generation and are referred to as generative AI. One such approach for content generation, introduced in the year 2014, is called generative adversarial networks (GANs), which consists of training a generator to create fake content that tries to mimic real content as closely as possible and a …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 31–41 Read article
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Money Laundering Transaction with Machine Learning
Abstract: This study discusses the use of machine learning algorithms to discover firms that are prone to money laundering. The purpose of this research is to develop, describe, and test a machine learning model for determining which bank transactions should be physically scrutinized for money laundering activities. To train a supervised machine learning model, three categories of historical data are required: legitimate "normal" transactions, transactions flagged as suspicious by the bank's …
Published in Current Trends in Information Technology · Vol. 14, Issue 2, 2024 · pp. 1–15 Read article
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Prediction of Customer Churn Using Machine Learning Classification Models
Abstract: Customer churn prediction is a critical task in both the telecommunication and medical industries, where retaining customers or patients is essential for ensuring long-term profitability and maintaining high-quality service. To address this, a range of machine learning models—including logistic regression, decision trees, random forests, gradient boosting machines, and support vector machines—were employed to accurately forecast churn behavior. Prior to model training, the dataset underwent thorough preprocessing, which included handling missing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 86–92 Read article
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SkinSight: Design and Implementation of an Intelligent Skin Type Detection System
Abstract: Identifying an individual’s skin type accurately is essential for creating personalized dermatological treatments and formulating skincare products that genuinely meet user needs. In this project, a real- time skin type classification system is developed using a combination of convolutional neural networks (CNNs) and modern computer vision techniques. The system processes live video streams, isolates the facial region through Haar cascade–based detection, and applies a series of preprocessing steps to enhance …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 35–45 Read article
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Gesture Identification in Children with Hearing Impairment: A Comparative Study
Abstract: Gestures are used during verbal communication naturally and spontaneously by individuals across age, culture and different background. Gestures and speech have a strong association and they share properties across temporal, structural and meaning aspects. Literature has shown pronounced link between gesture and speech however, there have been convincing and contradictory findings of the potential link of gestures and speech. So, there exists a need to further study gestural ability HI …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 10, Issue 1, 2021 · pp. 13–18 Read article
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Advancing Healthcare Systems: A Machine Learning Approach to Multi-Disease Prediction
Abstract: The integration of machine learning algorithms in healthcare has revolutionized the way we approach disease prediction and diagnosis. An attempt to employ machine learning techniques to forecast numerous diseases is presented in this study. A diverse dataset containing patient records, medical history, and relevant features for various diseases was used to develop predictive models. Feature selection and normalization were among the preprocessing methods used to clean and prepare the data. …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 1, 2025 · pp. 1–6 Read article
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Advanced Deep Learning Techniques for Sickle Cell Anaemia Detection
Abstract: Sickle Cell Anemia (SCA) is a prevalent genetic blood disorder characterized by the presence of abnormal hemoglobin, resulting in the distinctive sickle shape of red blood cells. Timely and accurate identification of Sickle Cell Anemia (SCA) is essential for effective management and treatment. This study presents a new method that utilizes Convolutional Neural Networks (CNNs), a deep learning model particularly effective for image analysis. The process involves using microscopic images …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 3, 2024 · pp. 9–15 Read article
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Various Bodyweight Training Effect on the Explosive Leg Strength of Badminton Players
Abstract: This study looked at how a six-week training program affected the leg strength of university badminton players in India. The program was done with thirty badminton players from Central University of Punjab who were between 18 and 24 years old. These badminton players did a training program that had them exercise three times a week. The training program had two types of exercises: exercises where the players held a position …
Published in Recent Trends in Sports · Vol. 3, Issue 2, 2026 · pp. 32–40 Read article
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Developing an AI-Based Novel Forecasting Framework for Surface Irregularity in Metal Matrix Materials
Abstract: Surface irregularity in metal matrix materials (MMM) signifies the deviations from smoothness, influencing structural integrity and performance frequently arising from the manufacturing process along with intrinsic material characteristics that influence effectiveness. Limitations in data, model interpretability and complexity are the difficulties that impede artificial intelligence (AI) based surface irregularity in MMM. In this study, we suggested a novel framework of Gaussian regression fused multi-strategy adaptive boosting classifier (GR-MABC) for the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 48–56 Read article
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Evaluating the Role of Arterial Duplex Ultrasound in Diabetic Foot Ulcer Patients with Normal Ankle Brachial Pressure Index and Peripheral Pulses
Abstract: Background: Requesting a arterial duplex scan has been a recent trend in management of diabetic foot ulcer, as it is considered the gold standard modality of investigation for diagnosing peripheral arterial diseases. Nevertheless, increased burden of the diabetic foot ulcer patients and limited availability of the facilities and trained radiologists prompts us to use this investigation judiciously. Most of the studies focus on role of abnormal ABPI as a predictor …
Published in Research and Reviews : Journal of Surgery · Vol. 11, Issue 2, 2022 · pp. 28–33 Read article
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Mammographic CADe And CADx for Identifying Microcalcification Using Support Vector Machine
Abstract: The second most frequent cause of death and disease in women worldwide is breast cancer. Effective detection is a crucial element in the successful treatment of cancer. X-ray mammography is the majorityfrequent method for breast cancer. Screenings because of its convenience, portability, and cost-effectiveness. The CADe and CADx techniques were designed to assist radiologists in improving the detection and screening of breast cancer. The goal is for breast cancer to …
Published in Journal of Communication Engineering & Systems · Vol. 10, Issue 2, 2020 · pp. 9–16 Read article