Ayoube Baalla^*, Mourad Najjaoui, Thami Ait-Taleb, Hassan Chaib

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.7, 2026, DOI:10.32604/fdmp.2026.083469 - 31 July 2026

Abstract The complex interplay of heat transfer mechanisms, namely conduction, natural convection, and radiation, within hollow block roofs exposed to solar irradiation gives rise to an inherently nonlinear thermal exchange problem. A key yet insufficiently explored question is the extent to which this nonlinearity governs the macroscopic thermal behavior of roofing systems. In this study, a computational investigation is conducted on two roof configurations incorporating five hollow block geometries representative of common construction practices in hot climatic regions. The objective is to identify the optimal design capable of minimizing heat losses and thereby enhancing the overall… More >

Mahander Kumar¹, Lal Khan^2,*, Mohammad Zubair Khan^3,*, Ibrahim Aljubayri⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.081699 - 27 July 2026

Abstract Aspect-Based Sentiment Analysis (ABSA) is a fundamental Natural Language Processing (NLP) task that aims to determine fine-grained sentiment polarity toward specific aspects mentioned in text. With the emergence of Large Language Models (LLMs) and transformer-based architectures, significant improvements have been achieved in contextual representation learning for sentiment analysis. However, existing LLM-inspired and transformer-based ABSA frameworks often suffer from inadequate aspect-context alignment, redundant feature integration, limited interpretability, and insufficient coordination between contextual and sequential modeling components. To address these challenges, this paper proposes two hybrid architectures, namely HABSA and AAC-HABSA, centered on a novel Adaptive Aspect… More > Graphic Abstract

Shuvodeep De^1,*, Agnivo Gosai^2,#, Karun Thankachan^3,#, Ramadan A. ZeinEldin⁴, Abdulaziz T. Almaktoom⁵, Mustafa Bayram⁶, Ali Wagdy Mohamed^7,8,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.080601 - 27 May 2026

Abstract Sentiment analysis (SA) has evolved from a niche text-classification task into a central problem in natural language processing, spanning multiple domains, modalities, and languages. This survey provides a comprehensive review of sentiment analysis methods from their origins in lexicon-based approaches through classical machine learning, deep learning architectures, pre-trained transformers, and the current era of large language models (LLMs). We formalize the SA problem across multiple granularity levels (document, sentence, and aspect) and present a taxonomy that encompasses classification, regression, aspect-based sentiment analysis (ABSA), emotion detection, and stance detection tasks across diverse domains including movie reviews,… More >

Oluwatosin Ahmed Amodu¹, Zurina Mohd Hanapi^1,*, Chedia Jarray², Huda Althumali³, Faten A. Saif ⁴, Raja Azlina Raja Mahmood¹, Mohammed Sani Adam⁵, Nor Fadzilah Abdullah⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.077054 - 27 May 2026

Abstract Non-terrestrial networks (NTNs)—including UAVs, HAPs, and satellite systems—are rapidly becoming key enablers of wide-area, resilient connectivity for large-scale IoT applications. As these platforms integrate with terrestrial networks to form space–air–ground architectures, optimization challenges related to trajectory, resource management, energy efficiency, and security become increasingly complex. Machine learning (ML) has emerged as a central tool for addressing these challenges by enabling adaptive, data-driven decision-making under uncertainty. This survey presents an optimization-centric review of ML-based NTN-assisted IoT systems focusing on aspect-specific datasets. Using a structured methodology involving dataset curation, keyword filtering, metadata analysis, and citation-based paper selection,… More >

Ayesha Kausar^*

Journal of Polymer Materials, Vol.43, No.1, 2026, DOI:10.32604/jpm.2026.078233 - 03 April 2026

Abstract Purpose of this novel review article is to unfold the current scientific worth of high performance polymer nanocomposite nanofibers, owing to growing scientific interests in this field. Accordingly, this state-of-the-art manuscript has been systematically categorized into distinct sections related to (i) fundamentals of carbonaceous nanoreinforcements, (ii) design-structure-property-performance aspects of different categories of polymer nanocomposite nanofibers (conducting polymers, thermoplastics, and thermosets with carbonaceous nanofillers (carbon nanotubes, graphene, fullerene), and then (iii) existing scientific worth (energy devices, electronics, space/defense, environmental sectors), future prospects, challenges, and conclusions. As per literature to date, polymer/carbonaceous nanocomposite nanofibers had myriad of advantageous physical… More > Graphic Abstract

Saifullah Tumrani^1,2,*, Abdul Jabbar Siddiqui^2,3,*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2025.075152 - 12 March 2026

Abstract Vehicle re-identification (ReID) is a challenging task in intelligent transportation, and urban surveillance systems due to its complications in camera viewpoints, vehicle scales, and environmental conditions. Recent transformer-based approaches have shown impressive performance by utilizing global dependencies, these models struggle with aspect ratio distortions and may overlook fine-grained local attributes crucial for distinguishing visually similar vehicles. We introduce a framework based on Swin Transformers that addresses these challenges by implementing three components. First, to improve feature robustness and maintain vehicle proportions, our Aspect Ratio-Aware Swin Transformer (AR-Swin) preserve the native ratio via letterbox, uses a… More >

Istvan Berkes^1,*, Bettina Piko^2,*

International Journal of Mental Health Promotion, Vol.27, No.11, pp. 1627-1643, 2025, DOI:10.32604/ijmhp.2025.071931 - 28 November 2025

Abstract Objectives: Parentification, a role reversal where children assume age-inappropriate duties in the family, is a significant childhood adversity often linked to disrupted developmental trajectories and poor mental health outcomes. Yet the complexity of parentification, influenced by various contextual factors, obscures a comprehensive understanding of its psychological consequences and its mental health aspects. The paper aims to map up-to-date research, synthesize key findings, and identify critical knowledge gaps. Methods: To that end, a systematic search was performed in Scopus, PsycINFO, PubMed, and EBSCO databases, and data was extracted and reviewed by two reviewers. The search yielded 29… More >

Božo Damjanović^*, Pejo Konjatić, Marko Katinić

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1735-1753, 2025, DOI:10.32604/cmes.2025.072256 - 26 November 2025

Abstract Ensuring the structural integrity of piping systems is crucial in industrial operations to prevent catastrophic failures and minimize shutdown time. This study investigates a transportation-damaged pipe exposed to high-temperature conditions and cyclic loading, representing a realistic challenge in plant operation. The objective was to evaluate the service life and integrity assessment parameters of the damaged pipe, subjected to 22,000 operational cycles under two daily charge and discharge conditions. The flaw size in the damaged pipe was determined based on a failure assessment procedure, ensuring a conservative and reliable input. The damage was characterized as a… More >

Dan Wang¹, Zhoubin Li¹, Yuze Xia^1,2,*, Zhenhua Yu^1,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5823-5845, 2025, DOI:10.32604/cmc.2025.071656 - 23 October 2025

Abstract Multimodal Aspect-Based Sentiment Analysis (MABSA) aims to detect sentiment polarity toward specific aspects by leveraging both textual and visual inputs. However, existing models suffer from weak aspect-image alignment, modality imbalance dominated by textual signals, and limited reasoning for implicit or ambiguous sentiments requiring external knowledge. To address these issues, we propose a unified framework named Gated-Linear Aspect-Aware Multimodal Sentiment Network (GLAMSNet). First of all, an input encoding module is employed to construct modality-specific and aspect-aware representations. Subsequently, we introduce an image–aspect correlation matching module to provide hierarchical supervision for visual-textual alignment. Building upon these components, More >

Jingxiang Zhou¹, Qiaoling Zhou^1,*, Chunlian Liang¹, Yulu Guo¹, Zhao Xiao², Yingfeng Xu¹

Structural Durability & Health Monitoring, Vol.19, No.4, pp. 953-983, 2025, DOI:10.32604/sdhm.2024.058501 - 30 June 2025

Abstract Streamlined box girders serve as a prevalent choice for the primary structural elements in large-span suspension bridge designs. With the increase in traffic demands, the design of such girders is evolving towards wider bridge decks and larger aspect ratios (B/D). To obtain more effective and aerodynamic design shapes for streamlined box girders, it is essential to investigate the impact of B/D on their aerodynamic performance. Accordingly, in this study we investigate the buffeting responses of large-span suspension bridges using girders of varying aspect ratios (B/D of 7.5, 9.3, and 12.7). First, the aerodynamic coefficients… More >