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67 articles for “Classification-based directives”
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Self-Learning SIEM System Using Association Rule Mining
Abstract: The rise of new security threats similar to polymorphic multi-step attacks, have made security something just more than perimeter defence, IDS/IPS, Firewalls, Anti-virus etc. Although, security techniques have evolved a lot, so have the attacks. Hence, a comprehensive solution is required wherein all the sensory controls can work in coherence. In this paper, we intend to propose a SIEM system with the self-learning capability which can produce optimized and efficient …
Published in Journal of Advanced Database Management & Systems · Vol. 2, Issue 2, 2015 · pp. 10–23 Read article
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Effective CBIR System Using Color Histogram and Distance Measures
Abstract: AbstractInterests to precisely retrieve desired images from databases of medical images are developing every day. Certain features define the images; on the basis of those, the retrieval of images is facilitated. These components incorporate texture, color, shape and region. A lot of work has been done in this direction to discover the new ways to use these features in image retrieval process. In this study, we exhibit an overview of …
Published in Journal of Web Engineering & Technology · Vol. 6, Issue 1, 2019 · pp. 11–14 Read article
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Survey on Retinal OCT Image Preprocessing, Segmentation, and Deep Learning Based Classification
Abstract: Optical coherence tomography (OCT) is a non-invasive technique that generates high-resolution, detailed cross-sectional images of biological tissues. By utilizing low-coherence interferometry, OCT enables visualization of tissue microstructure with micron-scale resolution, making it useful in various medical fields such as ophthalmology, cardiology, and dermatology. In ophthalmology, OCT is extensively used for diagnosing and monitoring retinal diseases like macular degeneration and diabetic retinopathy, allowing doctors to assess changes in tissue morphology over …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Identification and Extraction of Fingerprint Recognition by using Minutiae Features
Abstract: Fingerprints are the ancient and most widely used form of biometric identification. Everyone has unique, irremovable fingerprints. Most of the Automatic Fingerprint Recognition Systems are based on local ridge and bifurcations as features known as minutiae, marking minutiae accurately are very important when it comes to matching of similar or non-similar fingerprints. A critical step in automatic fingerprint matching is to reliably extract minutiae from the input fingerprint images. This …
Published in Recent Trends in Parallel Computing · Vol. 3, Issue 1, 2016 · pp. 22–26 Read article
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Blockchain Technology: Challenges and Opportunities
Abstract: Blockchain is a revolutionary digital, distributed network technology which has the power to replace third party trusted with mathematical concept and algorithms. It is considered as a change in every aspect in the life of humans. It is basically the peer-to-peer connection within a decentralized database. Blockchain provides us with the features of security, privacy, accessibility as well as immutability. Blockchains are mostly used for registering transactions, authenticating and validating …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 1, 2025 · pp. 21–30 Read article
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Concrete Oil and Gas Platforms in Offshore Marine Environment: A Review
Abstract: Abstract Offshore concrete structures have been successfully in use since 1973. Since then, 47 major concrete offshore structures were built worldwide. They were mostly used in the petroleum industry as drilling, extraction or storage units for crude oil or natural gas. Generally, offshore concrete structures are classified into fixed and floating structures. Fixed structures are mostly built as concrete gravity based structures where the loads are directly transferred through concrete …
Published in Journal of Offshore Structure and Technology · Vol. 4, Issue 1, 2017 · pp. 33–42 Read article
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Breast Cancer Detection and Multiple Classification Using CNN
Abstract: Although some efforts have been made in the form of preventative screening programs, breast cancer remains one of the rising causes of death in women. Computer-assisted diagnosis is needed because of the rapidly increasing number of mammograms that can be collected by these programs. Performance metrics are not significantly improved by computer aided detection methods designed to improve diagnosis without a large number of sequential readings. In this context, self-imaging …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 12, Issue 2, 2023 · pp. 28–38 Read article
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ML Model Comparison for Sentiment Analysis Across Diverse Datasets
Abstract: Analyzing sentiment is crucial for understanding public opinion on various issues in marketing, politics, and social sciences. This study compares the performance of seven different machine learning algorithms for sentiment classification, focusing on their effectiveness, accuracy, and complexity. The research is conducted on a pre-processed dataset with balanced text samples, utilizing feature extraction methods such as Term Frequency-Inverse Document Frequency (TF-IDF). The performance assessment criteria consist of accuracy, precision, recall, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 26–33 Read article
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Android Based Recognition of Nutrition Intake with Piezoelectric Sensor
Abstract: Ingestion rate, food intake level; these are the factors which are responsible for overweight. We design a system for the user which gives feedback about his eating habits. The sensor used here to detect swallows is MEAS piezoelectric sensor. This sensor is placed against throat. This system classifies food types in broad categories like liquid and solid food by using sensor data and also the application is developed which gives …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 4, Issue 2, 2016 · pp. 7–11 Read article
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An Effective Convolutional Neural Network for Identifying Cancer Blood Disorder Cells Using Microscopic Images
Abstract: Blood, bone marrow, and lymphatic systems are all impacted by hematological cancer is known as a cancer blood disorder. Blood malignancies and various blood disorders pose significant health challenges across all age groups. Early disease detection is essential for effective cancer blood disorder treatment and management. If a blood cancer is not identified in time, it may be hazardous. It results in abnormal white blood cell production by the bone …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 2, 2024 · pp. 29–35 Read article
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AI-Assisted Defect Detection in Polymer Composite Insulators Using an Optimised Ensemble Deep Learning Framework for Structural Health Monitoring
Abstract: Polymer composite insulators, particularly those made from silicone rubber and epoxy resins, are increasingly adopted in high-voltage transmission systems due to their superior electrical insulation, lightweight design, hydrophobicity, and environmental durability. Despite their advantages, these materials are susceptible to surface degradation, mechanical cracking, and flashover under prolonged exposure to environmental pollutants, thermal stress, and electrical aging. Accurate, real-time condition assessment of these composite insulators is critical for ensuring operational safety, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 253–261 Read article
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Machine Learning Techniques for Predicting Industries Based on Region
Abstract: In recent years, there has been a growing interest and emphasis on agricultural land preparation and its implementation among researchers, primarily due to various factors. These factors include an increased focus within the research community, a rising demand for agricultural land, and the significance of assessing soil health for ensuring robust crop production. Picture request is one such philosophy for soil and land prosperity examination. It is a staggering measure …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 1–8 Read article
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Differential Rooting Pattern Observed in Tissue Culture Regenerated Plantlets from Different Explants of Jatropha curcas L.
Abstract: Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 In an attempt to optimize an in vitro regeneration protocol, both direct and indirect, from different explants of Jatropha curcas L., different rooting patterns were observed from the regenerated plantlets in different concentrations of auxins. The rooting pattern was classified into four types based on their morphology as hairy fibrous roots, tap root-type, thin long roots, and thick short roots. Observations …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 3, Issue 1, 2013 · pp. 1–5 Read article
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Gesture-Based Cursor Control: A Comprehensive Review of Techniques and Applications
Abstract: Although hand gesture detection for man-machine interfaces has advanced recently, many systems still have issues with background and lighting. We have developed a rapid motion history image-based system to categorize dynamic hand motions and a face detection method to adaptively detect skin color. For the up, down, left-, and right-hand gesture classifiers, four sets of haar-like directional patterns were trained. To operate different household appliances, six hand gestures were defined, …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 3, Issue 1, 2025 · pp. 9–13 Read article
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Laser Beam Machining Techniques and Applications: A Review
Abstract: Laser beam machining (LBM) is the most common thermal energy-based non-contact, non-conventional machining process. The non-conventional manufacturing processes are used to remove extra material using a variety of mechanical, thermal, electrical, chemical, or combinations of these energies without the use of sharp cutting tools as is required for conventional manufacturing. With innovative approaches to manufacturing processes, it has transformed a number of industries. It is frequently used to machine a …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 28–35 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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An Evaluation of Sentiment Analysis in Online Reviews using FRN Algorithm
Abstract: The internet is rich in directional text (i.e., text containing opinions and emotions). World Wide Web provides volumes of text-based data about consumer preferences, stored in online review websites, web forums, blogs, etc. Sentiment analysis is a technique to classify people’s opinions in product reviews, blogs or social networks and has emerged as a method for mining opinions from such text archives. It uses machine learning methods combined with linguistic …
Published in Journal of Operating Systems Development & Trends · Vol. 1, Issue 1, 2014 · pp. 14–20 Read article
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Network Intrusion Detection System Using Decision Tree
Abstract: This paper presents a novel approach to network intrusion detection systems (NIDS) using advanced decision tree algorithms to address critical limitations in existing IDS solutions. Traditional IDSs often struggle with high false positive and negative rates, lack of scalability, and poor interpretability. Our proposed IDS leverages decision trees to enhance detection accuracy, interpretability, and scalability, thereby improving network security. Decision trees are chosen for their adaptive learning capabilities, transparent decision-making …
Published in Journal Of Network security · Vol. 12, Issue 2, 2024 · pp. 22–33 Read article
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EMOTION RECOGNITION FROM ELECTROENCEPHALOGRAM SIGNAL AND EYE MOVEMENT BASED ON DEEP LEARNING
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article
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Bearing Fault Diagnosis Using ANN and SVM with the Help of Wavelet Transform Based Features
Abstract: Many researchers use vibration signals as fault characteristics of any rotating bearing for fault detection and use various optimization techniques available for fault of bearing classification. The method of fault classification uses few neural network (NN) geometry and parameters necessary for the formulation. There is no derived formulation which can be used to select the optimal values for the network parameters. The parameters which are required to be calculated, impacts …
Published in Recent Trends in Electronics Communication Systems · Vol. 4, Issue 2, 2017 · pp. 26–34 Read article