105 articles for “Data Structures”

Review ArticleOpen accessIn the abstractDeep Learning in Early Alzheimer’s Disease’s Detection: A Comprehensive Survey of Classification, Segmentation and Feature Extraction MethodsRubab Hafeez, Sadia Waheed, Syeda Aleena Naqvi et al.Alzheimer’s disease is a deadly neurological condition, impairing important memory and brain functions. Alzheimer’s disease promotes brain shrinkage, ultimately leading to dementia. Dementia diagnosis typically takes 2.8-4.4 years after the first clinical indication. Advancements in computing and information technology have led to many techniques for studying Alzheimer's disease. Early identification and therapy are crucial for preventing Alzheimer's disease, as early-onset … …Journal of Computer Science, Vol. 21, Issue 5 · 26 Apr 2025 · 5,774 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEvaluating the Impact of Topography on Flooding in Owerri North, Imo State, Nigeria Using GIS and Remote Sensing TechniquesSylvanus Ibeabuchi IroThe aim of this study is to analyze the topographical contribution to floods in Owerri, North Imo State, Nigeria. Research was carried out to ascertain whether topographical elements played a role in the flooding in specific areas of Owerri North. As a result, very little research has looked at the effects of topography on flooding. Thus, there is a barrier … …American Journal of Environmental Sciences, Vol. 21, Issue 1 · 29 Jan 2025 · 7,208 accessesView PDF Cite

Research ArticleOpen accessIn the abstractResearch on the Link Between Economic Development Variables and the Rate of Access to Drinking Water in Rural Senegal Using Machine LearningAnabilaye Moussa Coly, Alioune Ly, Ndolane Diouf et al.After pre-processing a set of data collected from Senegalese state structures, official United Nations (UN), and world bank sites and after replacing missing values by interpolation using the mean between two values, we study the effect of macroeconomic development variables on the rate of access to drinking water in rural Senegal. To do this, we use Machine Learning (ML) techniques … …American Journal of Applied Sciences, Vol. 20, Issue 1 · 20 Dec 2023 · 6,208 accessesView PDF Cite

Research ArticleOpen accessIn the abstractMCMC-Fuzzy: A Fuzzy Metric Applied to Bayesian Network Structure LearningBeatriz Wilges, Ademar Crotti Junior, Silvia Modesto NassarBayesian network structure learning is considered a complex task as the number of possible structures grows exponentially with the number of variables. Two main methods are used for Bayesian network structure learning: Conditional independence, a method in which a structure is created consistently with independence tests performed on data; and the heuristic search method that explores the structure space. Hybrid … …Journal of Computer Science, Vol. 14, Issue 8 · 24 Aug 2018 · 8,247 accessesView PDF Cite

Research ArticleOpen accessIn the abstractStructural Performance of Double Laminated Glass Panels with EVA and PVB Interlayer in Four-Point Bending TestsTomáš Hána, Martina Eliášová, Zdeněk SokolMany examples of glass loadbearing structures such as handrails, panes, beams and columns can be found in modern architecture. Most of these elements are made of laminated glass panels. There is a general lack of knowledge about the transfer of shear forces between the glass plies in perpendicularly-loaded laminated panels. This transfer depends significantly on the stiffness of the polymeric … …International Journal of Structural Glass and Advanced Materials Research, Vol. 2, Issue 1 · 14 Aug 2018 · 13,283 accessesView PDF Cite

Research ArticleOpen accessIn the abstractIs Single Scan based Restructuring Always a Suitable Approach to Handle Incremental Frequent Pattern Mining?Shafiul Alom Ahmed, Bhabesh NathIncremental mining of frequent patterns has attracted the attention of researchers in the last two decades. The researchers have explored the frequent pattern mining from incremental database problems by considering that the complete database to be processed can be accommodated in systems’ main memory even after the database gets updated very frequently. The FP-tree-based approaches were able to draw more … …Journal of Computer Science, Vol. 17, Issue 3 · 12 Mar 2021 · 6,926 accessesView PDF Cite

Research ArticleOpen accessIn the abstractForecasting Corporate Financial Distress Using Explainable Machine Learning: Implications for Risk Management TechnologyKanjana Hinthaw, Warawut NarkbunnumFinancial distress prediction is a critical task in financial risk management, yet it remains challenging due to class imbalance, complex financial structures, and limited model interpretability. This study develops an integrated machine learning framework that combines feature selection, class imbalance handling, threshold optimization, and Explainable Artificial Intelligence (XAI) to improve both predictive performance and decision-making reliability. Using a dataset of … …Journal of Computer Science, Vol. 22, Issue 7 · 22 Jul 2026 · 1,135 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Detailed Preserving Medical Image Denoising Using Cluster-Wise PCA Thresholding and Iterative Mean FilteringMohit Sharma, Ayush Dogra, Anita Gupta et al.Image denoising is a vital process in medical imaging that involves removing noise or distortions introduced during image acquisition. Random noise can degrade image quality and reduce contrast, making accurate analysis more challenging. This paper presents a detail-preserving medical image denoising framework based on a hybrid methodology that combines cluster-wise Principal Component Analysis (PCA) thresholding with Iterative Mean Filtering (IMF). … …Journal of Computer Science, Vol. 22, Issue 4 · 18 Apr 2026 · 1,797 accessesView PDF Cite

Review ArticleOpen accessIn the abstractMachine Learning Integration for Precise Facial Micro-Expression RecognitionViola Bakiasi Shtino, Markela Muça, Senada BushatiThis study advances facial micro-expression recognition through innovative machine-learning techniques, addressing critical needs in psychology, security, and human-computer interaction. The purpose of this study is to improve micro-expression recognition through the optimization of feature transformation and machine learning algorithms. We introduce a novel approach combining Kernel Principal Component Analysis (KPCA) and Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction, … …Journal of Computer Science, Vol. 20, Issue 11 · 22 Oct 2024 · 5,601 accessesView PDF Cite

Research ArticleOpen accessIn the abstractVisible Derivative Spectroscopic Monitoring of the Old Woman Creek National Estuary During a Historically Dry Year and a Wet YearLorita Nivanthi Mihindukulasooriya, Brenna Shae Mabry, Madison Slocum, Joseph Daniel OrtizVisible derivative spectroscopy was used to interpret the sediment and phytoplankton assemblages within the old woman creek natural estuarine reserve during the summers of 2016 and 2017. A Varimax-rotated Principal Component Analysis (VPCA) of reflectance data collected from four sampling sites in 2016 identified three Varimax-rotated Principal Components (VPCs): Diatom + Illite (2016-VPC 1), Dinoflagellate Algae + Cyanobacteria + Cryptophytes … …American Journal of Environmental Sciences, Vol. 19, Issue 6 · 11 Jul 2024 · 4,672 accessesView PDF Cite