119 results for “Feature Vector”

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Review ArticleOpen accessIn the abstractHuman Activity Recognition at the Edge: A Systematic Review of Machine Learning Models, Deployment Constraints, and Latency Energy Accuracy Trade offsJose Antonio Rojas Guillén, Wini Ebelin Quispe Bautista, Arturo Gamarra MorenoHuman Activity Recognition (HAR) has become a key component of intelligent healthcare monitoring, assisted living, sports analytics, smart environments, and wearable computing. However, the migration of HAR models from cloud-centered architectures to edge, embedded, mobile, and wearable platforms introduces constraints related to computational capacity, memory footprint, battery consumption, inference time, and real-time responsiveness. This study presents a systematic literature review … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 593 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAssessing Supervised Classification Algorithms for Mangrove Detection and Differentiation from Other Forest Types in Paiton District, Probolinggo RegencyKaruniawan Puji Wicaksono, Fathor Rohman, Yasushi MitsudaRemote sensing provides an effective approach for monitoring forest cover dynamics, yet distinguishing mangroves from other forest types remains challenging in heterogeneous coastal landscapes. This study compares six supervised classification algorithms: Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Mixture Discriminant Analysis (MDA), Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) for mangrove detection in Paiton, … …OnLine Journal of Biological Sciences, Vol. 26, Issue 3 · 1 Sep 2026 · 844 accessesView PDF Cite

Research ArticleOpen accessIn the abstractMachine Learning Based Prediction of Catch Yields in Small Scale FisheriesEpifelward Niño Olaivar Amora, Patrick D. CernaSmall-scale fisheries are critical for food security and livelihoods but increasingly face threats from overfishing and environmental change. This study employed machine learning to predict catch yields in Cogtong Bay, Philippines, using 3,478 records collected in 2020–2021 that included species, gear, location, season, and weather data. Models developed in Python with scikit-learn and XGBoost compared Random Forest (RF), Extreme Gradient … …Journal of Computer Science, Vol. 22, Issue 8 · 24 Aug 2026 · 1,096 accessesView PDF Cite

Research ArticleOpen accessIn the abstractMoney Laundering Detection in Financial Institutions Using Machine LearningNoor Samer Masood, Rasha Hassan Sakr, Amal Abou EleneenThis research aims to develop a system based on machine learning techniques for the accurate detection and classification of money laundering transactions. This system utilizes real and synthetic financial data, including the IBM AML dataset and synthetic financial databases. The methodology included data collection and cleaning, feature extraction from transaction behavior, and training several classification algorithms, including Random Forest, Support … …Journal of Computer Science, Vol. 22, Issue 4 · 16 Apr 2026 · 2,325 accessesView PDF Cite

Research ArticleOpen accessIn the abstractTomato Leaf Disease Detection by Hybrid Ai and Ml TechnologyP. Loganathan, M. John Britto, Vinston RajaDiseases that affect plants contribute to productivity decline, but they can be managed with ongoing monitoring. It is time-consuming and prone to error to track plant diseases manually. Early disease detection using Artificial Intelligence (AI) and machine vision can lessen negative impacts while also overcoming some of the limitations of continuous human monitoring. Therefore, this study uses both Deep Learning … …Journal of Computer Science, Vol. 21, Issue 12 · 12 Feb 2026 · 1,881 accessesView PDF Cite

Research ArticleOpen accessIn the abstractDeveloping an Effective Churn Prediction Model for Telecommunications: Enhancing Customer Retention through Advanced Machine Learning TechniquesAshu Goyal, Anuj Gupta, Sharad Kumar et al.Customer churn poses a significant challenge for the telecommunications sector, resulting in substantial revenue losses and increased customer acquisition costs. This research creates an efficient churn prediction model that combines state-of-the-art machine learning with ensemble learning to maximize customer retention. With the IBM Telco Customer Churn dataset, several baseline models, including Gradient Boosting, AdaBoost, Logistic Regression, Random Forest, and Support … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 3,164 accessesView PDF Cite

Research ArticleOpen accessIn the abstractComparative Analysis of Neural Network Models for Predicting EUR/USD Direction: An Empirical StudyEl Badaoui Mohamed, Raouyane Brahim, El Moumen Samira, Bellafkih MostafaThis paper presents a rigorous comparative analysis of six feedforward neural network models for predicting the directional movement of the EUR/USD currency pair. The evaluated models include the Learning Vector Quantization, Cascade Neural Network, Feedforward Neural Network, Single Layer Perceptron, Multi-Layer Perceptron, and Radial Basis Function network. Utilizing daily historical data from April 2009 to May 2024, each model was … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 2,330 accessesView PDF Cite

Research ArticleOpen accessIn the abstractCardiovascular Diseases Identification Using Wavelet Optimization and Modify Cuckoo Search AlgorithmBanit Negi, Abhilekh Bartwal, Agya Ram Verma et al.The problem the author aims to solve is the extraction of discriminatory features in ECG (Electrocardiogram) signals for classification purposes. The scope of the work is to propose a new method for building wavelets that best reflect the discriminatory capacity of ECG signals. The approach involves optimizing the wavelets specifically for the classification function under consideration. To address the problem, … …Journal of Computer Science, Vol. 19, Issue 8 · 3 Aug 2023 · 5,403 accessesView PDF Cite

Research ArticleOpen accessIn the abstractTwitter Sentiment Analysis Using Machine Learning and Deep Learning TechniquesSafa Khalid Al Sarayrah, Noor Mahmoud Alkudah, Hesham Yousef Al-kharabshehThis research investigates the use of Machine Learning (ML) and Deep Learning, including BiLSTM approaches, for Sentiment Analysis (SA) of consumer reviews on social media sites. Businesses are increasingly depending on online reviews to determine customer satisfaction due to social media's explosive growth. We used three classification models, the assessment of these attitudes uses Naive Bayes (NB), Support Vector Machine … …Journal of Computer Science, Vol. 21, Issue 8 · 1 Sep 2025 · 6,813 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEcological Function Evaluation of Soil and Water Conservation Measures for Power Transmission and Transformation Project Construction Based on Remote Sensing and it’s Improvement PathYang Han, Songsong Wang, Yanhui Yang et al.Assessing ecological functions is critical for determining the efficacy of soil and water conservation measures, especially during the development of power transmission and transformation projects. Efficient conservation practices are essential for reducing ecological effects and guaranteeing sustainable development. This research aims to create a resilient model, Ecological Function Prediction for Conservation Effectiveness (EFP-CE) that will classify conservation effectiveness as either … …American Journal of Engineering and Applied Sciences, Vol. 18, Issue 1 · 17 Mar 2025 · 7,725 accessesView PDF Cite