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231 articles for “classification techniques”
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Green Hydrogen Revolution: Technological Developments and Environmental Evaluations
Abstract: As a major fuel source for the future, hydrogen energy has received great support from the public, government, and business community. Two significant barriers to cleaning hydrogen commercialization are the high cost of production and the slow expansion of the infrastructure. Numerous hydrogen production techniques are classified using color codes; the most popular option is green hydrogen, which is produced using sustainable resources like solar and wind energy. Green hydrogen …
Published in Journal of Nuclear Engineering & Technology · Vol. 14, Issue 3, 2024 · pp. 37–44 Read article
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Computer Aided Diagnosis of Breast Cancer using Machine Learning Techniques
Abstract: Breast cancer is one of the significant health problems that lead to early mortality in women, especially those between 40 and 55 years of age all over the world. In recent years, the number of breast cancer cases among women has risen significantly, making early and accurate diagnosis more important than ever. Computer-aided diagnostic (CAD) tools have become valuable in supporting radiologists by enhancing the precision of breast cancer detection. …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 2, 2025 · pp. 1–11 Read article
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A Comprehensive Review on Piezoelectric Composites for Energy Harvesting and Sensing
Abstract: The capacity of piezoelectric composites to transform mechanical energy into electrical energy and vice versa has drawn a lot of interest recently. This property makes them very appealing for use in energy harvesting and sensing applications. These materials combine the high piezoelectric performance of ceramics with the mechanical flexibility and processability of polymers or other matrices, enabling a wide range of practical uses in flexible electronics, wearable systems, and embedded …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 19–24 Read article
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ASSESSING OF FOREST STRUCTURE USING EARTH OBSERVATION DATA: ACASE STUDY IN MUNESSA FOREST, OROMIA REGION, ETHIOPIA
Abstract: Forest structure is essential for estimating forest-related carbon emissions, analyzing forest degradation, and quantifying the effectiveness of forest restoration initiatives. However, forest structure quantification is only limited to the specific area of interest without considering the whole forest coverage. Remote sensing data can easily deliver a large area to assess forest structure. Therefore, this study aims to assess forest structure of Munessa Natural Forest by integrating satellite based light detection …
Published in International Journal of Land Read article
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An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing Read article
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Enhancing Smart Grid Resilience Through AI-Based Fault Classification
Abstract: Traditional power grids can be developed into smart grids, and they are comprised of the latest information and communication technologies (ICTs), which are based on establishing the relationship between the conventional electricity systems along with the usage of smart meters and distributed generation. This dynamic improves energy efficiency and the integration of renewables. Well, the dynamic and reversible power injection from Distributed Energy Resources (DERs) creates substantial operational problems. These …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article
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Analysis and Identification of Malicious Mobile Applications Using Machines Learning
Abstract: Over the past few years, malware attacks on the Android platform have surged, posing significant risks to users' financial security, personal information, and device integrity. In the first half of 2019 alone, approximately 25 million smartphones were infected, highlighting the severity of these threats. The model ranks manifest features based on their frequency in normal and malicious apps, identifying key components that distinguish benign from malicious applications. To improve detection …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 17–24 Read article
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Visual Recognition with Convolutional Neural Networks for Object Detection
Abstract: Various research and development have taken place over the years on computer vision which is a branch of AI. AI disciplines like a vision system is applied in various fields like self-driving cars, face detection by social media apps and law enforcement software’s google lens and so on. The proposed system deals with design and implementation of an efficient way of training a GPU using python libraries to process and …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 07–13 Read article
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AI-Based Sentiment Analysis of Public Perception Under Bangabandhu Sheikh Mujibur Rahman
Abstract: Sheikh Mujibur Rahman, known as Bangabandhu, played a pivotal role in Bangladesh’s post-liberation period (1971–1975). Understanding public sentiment during his leadership is crucial for historical analysis. This study employs Artificial Intelligence (AI)-based Sentiment Analysis to examine public perception through archived newspapers, parliamentary speeches, and historical records. Using Natural Language Processing (NLP) techniques, including sentiment classification and opinion mining, we analyze textual data to assess the prevailing public mood during his …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 21–29 Read article
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Design and Optimization of Domain-Specific Languages for High-Performance Computing Applications
Abstract: The accelerating demand for computational power in scientific, engineering, and data-intensive domains has driven High-Performance Computing (HPC) systems toward unprecedented levels of parallelism and architectural complexity. Contemporary HPC platforms integrate multicore CPUs, many-core GPUs, accelerators, and deep memory hierarchies, creating significant challenges for software development and performance optimization. Traditional general-purpose programming languages and parallel programming frameworks provide low-level control over hardware resources but require extensive manual tuning, resulting in poor …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Assessing the Performance of DL Methods in Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a computer vision task that involves the automatic identification and classification of hand-written digits. The objective is to develop models capable of accurately recognizing and distinguishing digits handwritten by humans. With the development of machine learning and deep learning techniques, this field has advanced remarkably. The convolutional neural network (CNN) is the most often used technique for this purpose. By utilizing CNN, the model can learn …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 25–32 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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An Efficient CNN Model for Automated Cotton Leaf
Abstract: Timely and accurate identification of cotton leaf diseases are essential for maintaining healthy crop production and minimizing agricultural losses. Early detection allows farmers to take preventive or corrective measures, reducing the risk of disease spread and improving overall yield. In this study, we propose a Convolutional Neural Network (CNN) based model for the automated classification of cotton leaf diseases using image-based detection techniques. The model is trained on a diverse …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 3, 2025 · pp. 01–10 Read article
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Human Age and Gender Determination Using Fingerprints
Abstract: We present a review of technologies to determine human age and gender using fingerprints. Broadly two methodologies are reviewed i.e. Ridge based human age and gender determination and Image based human age and gender determination. Ridge based techniques uses ridge information with its variant statistics measures for classification of a human fingerprint into different classes of age groups and male/female distinction. These methods do not involve separate classifiers for classification …
Published in Journal of Advancements in Robotics Read article
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Transformer Health Monitoring System
Abstract: Rising demands for reliable and efficient power distribution in modern electric control grid increasingly call up for robust monitoring systems for critical substructure. Being a vital part of the power conduction system, transformer are subjected to mechanical, electrical, and environmental stresses, which, if not properly controlled, can cause failures. In this project, we propose a Transformer Health Monitoring System (THMS) using machine learning (ML) models and real-time monitoring method to …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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Liposomes Innovative Role as a Drug Delivery System: A Detailed Analysis
Abstract: The first nanomedicine to be approved for use in clinical settings was liposomes. These are the spherical vesicles with a bilayer of phospholipids enclosing a middle empty aqueous region. Because of their extraordinary potential to stop medication deterioration and lessen unwanted effects, liposomes are being utilized more and more for targeted drug distribution. For targeted drug delivery, the pharmaceuticals can be integrated into the liposomes' aqueous space or phospholipid bilayer. …
Published in Trends in Drug Delivery · Vol. 11, Issue 2, 2024 · pp. 25–32 Read article
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Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 Read article
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Classification and Detection of Brain Tumor using Convolutional Neural Network
Abstract: Tumors are masses created when brain cells multiply uncontrollably. A brain tumor is the medical term for this condition. Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Developing a treatment plan is essential to raising a patient's standard of living. Tumors in different regions of the body are evaluated using a variety of imaging techniques, with MRI pictures being utilized mostly for …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article
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Leveraging Deep Learning for Accurate Weed Identification
Abstract: Weed control is very important for all types of agricultural businesses. The project here revolves around the application of computer vision techniques and, more concretely, deep learning techniques, for the effective recognition and classification of weeds. The EfficientNetB4 architecture is an appropriate backbone as its scalability and performance optimization is adequate. The modifier used is Adam optimization algorithm which will serve as a pre- processor for the model. Weeds at …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 90–99 Read article