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344 articles for “Feature Detection”
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Cybersecurity of AI and IoT Integrated for Mechanical Industries
Abstract: By facilitating the concept of Industry 4.0, the intersection of artificial intelligence (AI) and the Internet of Things (IoT) has changed the mechanical industries. When combined, these technologies are advancing process optimization, predictive maintenance, real-time condition monitoring, and smarter automation. In order to give proactive system control and intelligent decision-making, AI algorithms mine large datasets generated via IoT devices for relevant patterns. In the meanwhile, IoT guarantees smooth communication between …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 27–33 Read article
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Box Plots: An Introduction to the Visual EDA Wonder
Abstract: A box plot, also known as a box-and-whisker plot, is a widely used statistical graphic that provides a concise summary of the distribution of numerical data. By displaying key descriptive measures such as the median, quartiles, interquartile range (IQR), minimum and maximum values, and potential outliers, box plots allow researchers to quickly understand the spread and central tendency of a dataset. They are especially useful when comparing distributions across multiple …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 20–30 Read article
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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Automated Fake News Detection System
Abstract: The classification of fake news on social media platforms has drawn a lot of attention recently because it is so simple to put false stuff there. In addition, they prefer social media to traditional television as their news source of choice. These patterns have increased academics' understanding of fake news and inspired an increase in interest in its identification. The primary goal of this work was to classify incorrect information …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 1, 2023 · pp. 70–78 Read article
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Pothole Detection utilising Machine Learning: A Review
Abstract: Potholes must be found and fixed quickly in order to maintain infrastructure, maximize transportation systems, and guarantee road safety. Using the Sequential API and the Keras library, this study presents a neural network model for pothole detection. Convolutional layers with ReLU activation, global average pooling, dense layers with dropout, and softmax activation for binary classification make up the model architecture. Image loading, resizing, array conversion, labeling, shuffling, normalization, and one-hot …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 1, 2025 · pp. 35–43 Read article
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Evaluating the Efficiency of LLMs-SA (Sentiment Analysis) via Social Media Texts
Abstract: Sentiment analysis (SA) is becoming popular in business and scientific communities as the processing of natural language (NLP), computational linguistics, text analytics, image-based processing or video- based processing is used in extracting and mining subjective information in the web, social network, etc. It is able to detect positive, negative or neutral information and can be selected to absorb polarity, sentiments, urgency and goals of mount importance. The majority of the …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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Intelligent Water Distribution Management using IoT
Abstract: Water plays a vital role in agriculture, making its efficient management essential for sustainable crop production. However, undetected leaks in irrigation systems can result in significant water loss, irregular watering of fields, soil degradation, and reduced crop yield. Conventional methods like manual inspection are not only labor-intensive but also ineffective in identifying leaks promptly – emphasizing the need for a smarter and automated approach to water monitoring. To address this …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 1, 2026 · pp. 18–27 Read article
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Brain Stroke Detection Using Deep Learning and Grad-CAM Explainability Framework
Abstract: Seconds matter when a brain stroke occurs; it is a race against time where rapid, precise intervention is the only way to preserve a patient’s quality of life. This research introduces a deep learning framework designed to act as a vital ally for clinicians, providing automated, high-speed stroke detection through brain MRI analysis. At the heart of our approach is EfficientNetB0, a sophisticated neural network chosen for its ability to …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 8–14 Read article
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Fake News Detection System Using MultinomialNB and Django Framework
Abstract: The emergence of the World Wide Web and the rapid growth of online platforms have transformed the landscape of news dissemination. However, the rise of social media has also led to an overwhelming influx of potentially unreliable information, making it increasingly challenging to verify the truthfulness of articles. This verification process has become a daunting task, necessitating a thorough examination of various domain-specific aspects to ascertain the credibility of news …
Published in Current Trends in Information Technology · Vol. 15, Issue 1, 2025 · pp. 23–32 Read article
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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article
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Assessing of Forest Structure Using Earth Observation Data: A Case Study in Munessa Forest, Oromia Region, Ethiopia
Abstract: Understanding forest structure is crucial for estimating carbon emissions associated with forests, assessing forest degradation, and evaluating the success of forest restoration efforts. However, forest structure quantification is limited to the area of interest without considering the whole forest coverage. Forest structure may be easily assessed over a wide area using data from remote sensing. Thus, by combining ground observation with satellite-based light detection and ranging (LiDAR) and Sentinel 2 …
Published in International Journal of Land · Vol. 2, Issue 1, 2025 · pp. 28–37 Read article
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Flying Drone Using KK Flight Controller
Abstract: This paper presents the design, development, and testing of a quadcopter drone using the KK2.1.5 flight controller, with an emphasis on stability and educational value. The KK2.1.5 controller features are inbuilt LCD screen, inbuilt programming, enabling direct configuration and tuning without the need for a computer interface, which makes it highly suitable for beginners and students. The drone is built using a modular frame architecture, which allows for easy replacement …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 20–25 Read article
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Detection of Pneumonia in COVID-19 Patients Using X-ray Images
Abstract: This study explores the use of chest X-ray image analysis and deep learning methods to identify pneumonia in COVID-19 patients. Due to the pandemic, Proper as well as immediate examination of COVID-19 is now essential for patient care and disease control. This study proposes a novel approach that uses convolutional neural networks (CNNs) to automatically predict pneumonia in COVID-19 patients using chest X-ray images. In this study, an X-ray of …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 13–23 Read article
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Harmonic Compensation in Grid Interconnected DG Units by Closed Loop Control
Abstract: This paper deals with improvement of power quality problem namely harmonic problem using distributed generation as their source of electricity. The harmonics occur in such a system because of the nature of loads connected. There are many power quality problems; out of which harmonics normally caused by nonlinear loads like variable frequency drives, fluorescent lightning, office computers etc. have adverse effects on the power quality. Also, harmonic detection and prediction …
Published in Journal of Power Electronics and Power Systems · Vol. 7, Issue 1, 2017 · pp. 9–17 Read article
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Feature Selection and Weighted Based Optimized Weight based Multi-Tier Stacked Ensemble (WMTSE) Classification for Twitter Sentiment Analysis
Abstract: AbstractThis research work concentrates on both feature selection and classification methods for utilizing twitter data. A new classifier is introduced for classifying “tweets” into positive, negative and neutral sentiment. The system contains four steps: Preprocessing by Tokenization, Text Cleaning, Part of Speech (PoS) Tagging, Stemming and Stop Words Removal, Feature Extraction by Bag-of-words (BoW), Lexicon-based features and Term Frequency- Inverse Document Frequency(TF-IDF), Feature Selection by Binary Swallow Swarm Optimization (BSSO) …
Published in Journal Of Network security · Vol. 8, Issue 3, 2020 · pp. 20–23 Read article
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An Automation Detection for Sign Language Using AI
Abstract: Sign language recognition has attracted considerable interest because of its ability to facilitate communication between the deaf community and the public, thereby bridging communication divides. Traditional approaches to sign language recognition often face challenges in accurately interpreting the complex and nuanced gestures inherent in sign languages. However, recent advancements in deep learning techniques have shown promising results in improving the accuracy and robustness of sign language recognition systems. This study …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 1–14 Read article
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Advances in Lung Cancer Detection and Diagnosis: An Integrative Approach Using Computational Chemistry, Statistics, Bioinformatics, Artificial Intelligence, and Machine Learning
Abstract: Lung cancer is still one of the most common and lethal cancers globally, accounting for more than a million deaths each year. Prompt detection is important, and imaging techniques like chest X-rays, MRIs, PETs, CTs, and molecular imaging have become important tools. But still, even though all these techniques do not provide an accurate classification of the lesion, they have led to the development of computer-based high-resolution image analysis. Computer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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A Correlation of Genetic and Clinical Perspective of Becker’s Muscular Dystrophy
Abstract: Patients from neurogenetic clinic on the basis of clinical features, elevated serum CPK level and electromyographic features were recruited for the study. Molecular genetic testing was performed by Multiplex Polymerase Chain Reaction (PCR) technique. A total of 60 patients were recruited in this study out of which 36 patients had deletion and 24 patients had no deletion. Our data showed that there is no correlation between clinical severity/laboratory findings and …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 9, Issue 1, 2019 · pp. 33–37 Read article
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A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
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Diffusion-Based Enhancement of Low-SNR Time- Frequency Signals
Abstract: Traditional enhancing techniques are useless in low signal-to-noise ratio (LSNR) situations because noise drastically interferes with communication signals. Based on an enhanced DiffBIR model, this paper suggests a dual-stage signal improvement approach that combines diffusion with deep learning. By combining the Inception module for multi-scale feature extraction with the Pixel Fusion Attention (PFA) module for significant region highlighting, the model improves signal recovery in the time- frequency domain. Experiments show …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 15–27 Read article