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Research ArticleOpen accessIn the abstractSystematic Literature Review of Graph Neural Networks in Disaster Management: Methods, Applications, and Future DirectionsSularno, Wendi Boy, Putri Anggraini et al.The increasing frequency and complexity of natural disasters underscore the urgent need for intelligent systems that support timely and effective decision-making. Graph Neural Networks (GNNs) have emerged as a powerful deep-learning paradigm for modeling spatial and relational data, offering distinct advantages for disaster management. This study presents a Systematic Literature Review (SLR) of GNN-based approaches for disaster mitigation, emergency response, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,036 accessesView PDFCite
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 PDFCite
Research ArticleOpen accessIn the abstractComplex SQL-NoSQL Query Translation for Data Lake ManagementNurhadi, Rabiah Abdul Kadir, Ely Salwana Mat SurinA data lake refers to an extremely large data resource or repository. Data lakes store large amounts of data and use advanced analytics to pair data from multiple sources with different types of structured, semi-structured, and unstructured information. NoSQL databases such as Mongodb, Redis, Neo4j, and Cassandra are nontabular and they store data differently rather than use relational tables. NoSQL … …Journal of Computer Science, Vol. 18, Issue 12 · 19 Dec 2022 · 9,277 accessesView PDFCite
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 · 6,923 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Open-Source Online Examination System to Meet the Integrity Demands of E-LearningAbdul Wahab MuzaffarThe rise of online learning platforms and the growing demand for remote education emphasize the importance of online exam-proctoring tools. Online proctoring tools presented in the literature require high internet speed and specialized hardware support, posing accessibility challenges for individuals in developing countries. This study aims to develop a solution that relies on something other than high internet speed and … …Journal of Computer Science, Vol. 20, Issue 6 · 3 Apr 2024 · 7,391 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetermination of Neuromuscular Diseases Using Complexity of Electromyogram SignalsKawser Ahammed, Mosabber Uddin AhmedCharacterization of Electromyogram (EMG) signals is important for identifying neuromuscular diseases. Although various techniques were implemented for classification, none of them were implemented in the complexity domain. In this study, characterization of EMG signals recorded from healthy, neuropathic and myopathic subjects has been performed in complexity domain based on Multiscale Entropy (MSE) method. To do this, the multiscale entropy method … …Neuroscience International, Vol. 10, Issue 1 · 7 Dec 2019 · 7,931 accessesView PDFCite
Research ArticleOpen accessIn the abstractONCObc-ST: An Improved Clinical Reasoning Algorithm Based on Select and Test (ST) Algorithm for Diagnosing Breast CancerOlaide Nathaniel Oyelade, Sunday Adeyemi AdewuyiThe need for an accurate reasoning algorithm is usually necessitated by the sensitivity of domain of (medicine as example) application of such algorithms. Most reasoning algorithms for medical diagnosis are either limited by their techniques or accuracy and efficiency. Even the Select and Test (ST) algorithm which is considered a more approximate reasoning algorithm is also limited by its approach … …Current Research in Bioinformatics, Vol. 8, Issue 1 · 15 Apr 2019 · 7,162 accessesView PDFCite
Research ArticleOpen accessIn the abstractImpact of Information Technology Training on Staff Engagement and Productivity: A Study on Some Selected Commercial Banks in Chattogram CityMd. Shahnur Azad Chowdhury, Md. Shariful Haque, Nazneen Jahan Chaudhury et al.This study aims to examine the effect of Information Technology (IT) training on the staff engagement and productivity of bank employees in Chattogram, Bangladesh. Extensive literature related to technological advancement, training, and employee performance were reviewed from the database and website to develop a conceptual model to check the effect. The relationship between the performance of the employee and IT … …Journal of Computer Science, Vol. 18, Issue 4 · 18 Apr 2022 · 6,193 accessesView PDFCite
Research ArticleOpen accessIn the abstractVERBO: Voice Emotion Recognition dataBase in Portuguese LanguageJosé R. Torres Neto, Geraldo P.R. Filho, Leandro Y. Mano, Jó UeyamaThe recognition of human emotional traits based on Affective Computing is being carried out by computational systems that are able to interpret and react intelligently to the context of the user. Speech Emotion Recognition systems are capable of transforming speech signal data into information related to the feelings of individuals in specific situations. However, the emotional expression of a human … …Journal of Computer Science, Vol. 14, Issue 11 · 2 Nov 2018 · 9,453 accessesView PDFCite
Research ArticleOpen accessIn the abstractVariants Within over a Hundred Complete COVID-19 Genomes and the Impact on Health SecuritySayed A.M. Amer102 complete COVID-19 genomes have been collected from the viral genomes database to track and characterize novel variants. The data were treated bioinformatically so that 172 variants, with 127 unique and 45 polymorphic variants were found. The 127 unique variants consist of 76 missense, 39 synonymous, 6 non-coding, 5 deletions and 1 insertion. The 45 polymorphic variants consist of 25 … …American Journal of Biochemistry and Biotechnology, Vol. 17, Issue 1 · 28 Jan 2021 · 6,592 accessesView PDFCite