Research ArticleOpen accessEvery word in the titleA Qualitative Assessment of VANET Routing Protocols Under Different Mobility ModelsMeriem Houmer, Moulay Lahcen HasnaouiVehicular Ad-hoc Networks (VANET) is an advanced wireless network that came to increase traffic safety, efficiency and to improve driving experience. The high mobility of nodes is the major characteristic in these networks. The aim of this paper is to figure out the impact of various mobility models on the performance of Ad-hoc On-demand Distance Vector (AODV), Cluster-Based Directional Routing … …Journal of Computer Science, Vol. 15, Issue 1 · 23 Jan 2019 · 7,458 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleComparative Assessment of Analytical models for the ULS Resistance Verification of Structural Glass Elements under Variable LoadsChiara Bedon, Claudio AmadioThe design of glass structures, due to the intrinsic material properties, is mainly governed by the typical tensile brittle behavior of the material. In this regard, a currently open question related to the use of glass in buildings as a load-bearing constructional material, is represented by the correct estimation of static fatigue phenomena due to a generic combination of design … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 1 · 16 Mar 2017 · 7,761 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDigital Maturity Assessment – A Case StudyFadwa Zaoui, Nissrine SouissiThe digital transformation is in progress; thisexercise is very agile in the sense that it requires the adoption of one of thekey precepts of agility and that supposes to include the digital transformationin an iterative and incremental logic. This can only be achieved if there isevaluation and adjustment accordingly. This is the focus of this study, theassessment of digital maturity, … …Journal of Computer Science, Vol. 18, Issue 8 · 24 Aug 2022 · 7,514 accessesView PDFCite
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 · 1,130 accessesView PDFCite
Research ArticleOpen accessIn the abstractIoT-Integrated CNN Deep Learning for Automated Breast Cancer Detection and DiagnosisYamini Kalva, R. Ganesh Babu, Sindhu V. et al.Breast cancer continues to be a primary cause of death in women, requiring prompt and accurate diagnosis to enhance treatment results. Traditional diagnostic techniques depend on manual assessment, which leads to possible misclassification, significant inter-observer variability, and delays in decision-making. Current deep learning models, including CNNs, frequently experience feature loss, gradient declining and restricted adaptability to real-time data. To overcome … …Journal of Computer Science, Vol. 22, Issue 4 · 30 Mar 2026 · 1,753 accessesView PDFCite
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 abstractRemote Sensing Image Classification Using Convolutional Neural Network (CNN) and Transfer Learning TechniquesMustafa Majeed Abd Zaid, Ahmed Abed Mohammed, Putra SumariThis study investigates the classification of aerial images depicting transmission towers, forests, farmland, and mountains. To complete the classification job, features are extracted from input photos using a Convolutional Neural Network (CNN) architecture. Then, the images are classified using Softmax. To test the model, we ran it for ten epochs using a batch size of 90, the Adam optimizer, and … …Journal of Computer Science, Vol. 21, Issue 3 · 11 Feb 2025 · 10,117 accessesView PDFCite
Research ArticleOpen accessIn the abstractFusing CNN Models for Improved Parkinson’s Disease Detection from Handwritten FeaturesSabrina Benredjem, Tahar MekhazniaNeurodegenerative Diseases (NGD) are a group of progressive neurological disorders, including cognitive decline as Alzheimer’s Disease (AD) and Parkinson’s Disease (PD) that result in the progressive loss of neuronal structure or function. This can lead to a variety of symptoms, in this study we are interested in PD one of the neurological diseases that causes the loss of dopamine-producing neurons … …Journal of Computer Science, Vol. 21, Issue 2 · 22 Jan 2025 · 6,306 accessesView PDFCite