Omar Darwish¹, Shorouq Al-Eidi², Abdallah Al-Shorman¹, Majdi Maabreh³, Anas Alsobeh⁴, Plamen Zahariev⁵, Yahya Tashtoush^6,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-21, 2026, DOI:10.32604/cmc.2025.068266 - 10 November 2025

Abstract Covert timing channels (CTC) exploit network resources to establish hidden communication pathways, posing significant risks to data security and policy compliance. Therefore, detecting such hidden and dangerous threats remains one of the security challenges. This paper proposes LinguTimeX, a new framework that combines natural language processing with artificial intelligence, along with explainable Artificial Intelligence (AI) not only to detect CTC but also to provide insights into the decision process. LinguTimeX performs multidimensional feature extraction by fusing linguistic attributes with temporal network patterns to identify covert channels precisely. LinguTimeX demonstrates strong effectiveness in detecting CTC across… More >

Mohamed Ezz¹, Meshrif Alruily^1,*, Ayman Mohamed Mostafa^2,*, Alaa S. Alaerjan¹, Bader Aldughayfiq², Hisham Allahem², Abdulaziz Shehab²

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-28, 2026, DOI:10.32604/cmc.2025.063189 - 10 November 2025

Abstract Automated essay scoring (AES) systems have gained significant importance in educational settings, offering a scalable, efficient, and objective method for evaluating student essays. However, developing AES systems for Arabic poses distinct challenges due to the language’s complex morphology, diglossia, and the scarcity of annotated datasets. This paper presents a hybrid approach to Arabic AES by combining text-based, vector-based, and embedding-based similarity measures to improve essay scoring accuracy while minimizing the training data required. Using a large Arabic essay dataset categorized into thematic groups, the study conducted four experiments to evaluate the impact of feature selection,… More >

Jawad Ali^1,*, Ioan-Lucian Popa^2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 857-889, 2025, DOI:10.32604/cmes.2025.064604 - 30 October 2025

Abstract With the rapid growth of urbanization, smart city development has become a strategic priority worldwide, requiring complex and uncertain decision-making processes. In this context, advanced decision-support tools are essential to evaluate and prioritize competing initiatives effectively. To support effective prioritization of smart city initiatives under uncertainty, this study introduces a robust decision-making framework based on the t-arbicular fuzzy (t-AF) set—a recent extension of the t-spherical fuzzy set that incorporates an additional parameter, the radius , to enhance the representation of uncertainty. Dombi-based operational laws are formulated within this context, leading to the development of four… More >

Anna Elisa Silva, Eduardo Thiago Formigari, João Pedro Mayer Camacho Araújo, Dagoberto de Oliveira Silva, Jürgen Andreaus, Eduardo Guilherme Cividini Neiva^*

Journal of Renewable Materials, Vol.13, No.10, pp. 1899-1912, 2025, DOI:10.32604/jrm.2025.02025-0130 - 22 October 2025

Abstract Here, we report a comprehensive study on the characterization of cotton biomass residue, its conversion into carbon-based materials via pyrolysis, and its application as an electrochemical sensor for ascorbic acid (AA). The compositions, morphologies, and structures of the resulting materials were investigated using XRD, FTIR, TGA, SEM, and EDS. Pyrolysis was carried out in an air atmosphere at different temperatures (300°C and 400°C) and durations (1, 60, and 240 min), leading to the transformation of lignocellulosic cotton residue into carbon-based materials embedded with inorganic nanoparticles, including carbonates, sulfates, chlorates, and phosphates of potassium, calcium, and… More > Graphic Abstract

Rodrigo Rafael da Silva^1,*, Gabriela Carvalho Maia de Queiroz¹, Amanda Cibele da Paz Sousa¹, Antônio Gustavo de Luna Souto¹, Francisco Hélio Alves de Andrade ², Francimar Maik da Silva Morais¹, Rita Magally Oliveira da Silva Marcelino¹, Fagner Nogueira Ferreira¹, Alex Alvares da Silva³, Maria Isabela Batista Clemente¹, Baltazar Cirino Junior¹, Wedson Aleff Oliveira da Silva¹, Mateus de Freitas Almeida dos Santos¹, José Francismar de Medeiros^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.9, pp. 2797-2814, 2025, DOI:10.32604/phyton.2025.068089 - 30 September 2025

Abstract Due to its tolerance to water deficit and salinity, sorghum is considered a suitable crop for cultivation in regions affected by these stress conditions, enabling the efficient use of limited water resources. This study evaluated the resilience of the sweet sorghum cultivar BRS 506 under water deficit and salinity stress, focusing on water relations and yield performance in semiarid conditions. A randomized complete block design was employed in a 3 × 3 factorial arrangement with four replicates. Treatments consisted of three levels of irrigation water salinity (1.50, 3.75, and 6.00 dS m⁻¹) and three irrigation levels… More >

Xinlong Wang¹, Xiaohang Qu¹, Chuandong Lin^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.011311

Abstract The lattice Boltzmann method (LBM) has been extensively utilized in various fields, including the droplet dynamics [1–4]. At present, significant challenges persist in accurately resolving interfacial dynamics during droplet collisions—including deformation [5], breakup process [6] and capturing microscale details [7] of contact line motion during droplet-wall interactions. In this work, the non-orthogonal multiple relaxation time lattice Boltzmann method is used to study droplets impacting superhydrophobic walls with different characteristic of surface protrusion. The horizontal displacement, maximum spreading length, and the contact time are probed in the process of droplet collisions under various conditions of Weber More >

Edo Bedzra^1,2,*, Herra Javed^3,4, James E. O’Brien^1,2, Taufiek Konrad Rajab^3,4

Congenital Heart Disease, Vol.20, No.4, pp. 441-446, 2025, DOI:10.32604/chd.2025.071035 - 18 September 2025

Abstract A bicuspid aortic valve, from autologous tissue, with growth potential can be constructed using the simple, and reproducible telescoping arterial trunk technique. More >

Yazeed Alkhrijah^1,2, Shehzad Khalid³, Syed Muhammad Usman^4,*, Amina Jameel³, Danish Hamid⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 1113-1141, 2025, DOI:10.32604/cmes.2025.068726 - 31 July 2025

Abstract Arabic Sign Language (ArSL) recognition plays a vital role in enhancing the communication for the Deaf and Hard of Hearing (DHH) community. Researchers have proposed multiple methods for automated recognition of ArSL; however, these methods face multiple challenges that include high gesture variability, occlusions, limited signer diversity, and the scarcity of large annotated datasets. Existing methods, often relying solely on either skeletal data or video-based features, struggle with generalization and robustness, especially in dynamic and real-world conditions. This paper proposes a novel multimodal ensemble classification framework that integrates geometric features derived from 3D skeletal joint… More >

Fay Aljomah, Lama Aldhafeeri, Maha Alfadel, Sultanh Alshahrani, Qaisar Abbas^*, Sarah Alhumoud^*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5317-5335, 2025, DOI:10.32604/cmc.2025.062478 - 30 July 2025

Abstract Dialectal Arabic text classification (DA-TC) provides a mechanism for performing sentiment analysis on recent Arabic social media leading to many challenges owing to the natural morphology of the Arabic language and its wide range of dialect variations. The availability of annotated datasets is limited, and preprocessing of the noisy content is even more challenging, sometimes resulting in the removal of important cues of sentiment from the input. To overcome such problems, this study investigates the applicability of using transfer learning based on pre-trained transformer models to classify sentiment in Arabic texts with high accuracy. Specifically,… More >

Wilhelm Mistiaen^*

Congenital Heart Disease, Vol.20, No.3, pp. 305-323, 2025, DOI:10.32604/chd.2025.064675 - 11 July 2025

Abstract The presence of a bicuspid aortic valve (BAV) is the most common congenital heart anomaly, which can remain asymptomatic for decades, if it is not a part of a syndrome, such as Turner syndrome or genetic connective tissue disorders. There are several classifications for BAV, each with its advantages and drawbacks. The condition can lead to valvular malfunction such as regurgitation and stenosis, but is often associated with dilatation of the aortic root, the ascending aorta, the aortic arch, or a combination. Altered flow patterns due to the valve dysfunction as well as the breakdown… More >