Abdu Salam¹, Fahd M. Aldosari², Donia Y. Badawood³, Farhan Amin^4,*, Isabel de la Torre^5,*, Gerardo Mendez Mezquita⁶, Henry Fabian Gongora⁶

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073342 - 10 February 2026

Abstract Lung cancer remains a major global health challenge, with early diagnosis crucial for improved patient survival. Traditional diagnostic techniques, including manual histopathology and radiological assessments, are prone to errors and variability. Deep learning methods, particularly Vision Transformers (ViT), have shown promise for improving diagnostic accuracy by effectively extracting global features. However, ViT-based approaches face challenges related to computational complexity and limited generalizability. This research proposes the DualSet ViT-PSO-SVM framework, integrating a ViT with dual attention mechanisms, Particle Swarm Optimization (PSO), and Support Vector Machines (SVM), aiming for efficient and robust lung cancer classification across multiple… More >

Fei Yu^1,2,3,*, Zhenya Diao^1,2, Hongrun Wu^1,2,*, Yingpin Chen^1,3, Xuewen Xia^1,2, Yuanxiang Li^2,3,4

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.072593 - 10 February 2026

Abstract Feature selection serves as a critical preprocessing step in machine learning, focusing on identifying and preserving the most relevant features to improve the efficiency and performance of classification algorithms. Particle Swarm Optimization has demonstrated significant potential in addressing feature selection challenges. However, there are inherent limitations in Particle Swarm Optimization, such as the delicate balance between exploration and exploitation, susceptibility to local optima, and suboptimal convergence rates, hinder its performance. To tackle these issues, this study introduces a novel Leveraged Opposition-Based Learning method within Fitness Landscape Particle Swarm Optimization, tailored for wrapper-based feature selection. The… More >

Herlina Marta¹, Novita Indrianti^2,*, Allifiyah Josi Nur Aziza³, Enny Sholichah⁴, Titik Budiati³, Achmat Sarifudin⁵, Yana Cahyana¹, Nandi Sukri¹, Aldila Din Pangawikan¹

Journal of Renewable Materials, Vol.14, No.1, 2026, DOI:10.32604/jrm.2025.02025-0145 - 23 January 2026

Abstract Corn starch (CS) is a renewable, biodegradable polysaccharide valued for its film-forming ability, yet native CS films exhibit low mechanical strength, high water sensitivity, and limited thermal stability. This study improves CS-based films by blending with poly(vinyl alcohol) (PVA) or glycerol (GLY) and using citric acid (CA) as a green, non-toxic cross-linker. Composite films were prepared by casting CS–PVA or CS–GLY with CA at 0%–0.20% (w/w of starch). The influence of CA on physicochemical, mechanical, optical, thermal, and water barrier properties was evaluated. CA crosslinking markedly enhanced the tensile strength, water resistance, and thermal stability More > Graphic Abstract

Nur Afikah Juhari, Khairul Nizam Tahar^*

Revue Internationale de Géomatique, Vol.35, pp. 1-11, 2026, DOI:10.32604/rig.2026.070991 - 19 January 2026

Abstract The use of Unmanned Aerial Vehicles (UAVs) in photogrammetry has grown rapidly due to enhanced flight stability, high-resolution imaging, and advanced Structure from Motion (SfM) algorithms. This study investigates the potential of UAVs as a cost-effective alternative to Terrestrial Laser Scanners (TLS) for 3D building reconstruction. A 3D model of Bangunan Sarjana was generated in Agisoft Metashape Professional v.2.0.2 using 492 aerial images captured at flying altitudes of 40, 50, and 60 m. Ground control points were established using GNSS (RTK-VRS), and Total Station measurements were employed for accuracy validation. The results indicate that the 60 More >

Chee Chin Lim^1,2,*, Hui Wen Tiu¹, Qi Wei Oung^1,3, Chiew Chea Lau⁴, Xiao Jian Tan^2,5

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.070468 - 12 January 2026

Abstract Breast cancer remains one of the leading causes of cancer mortality world-wide, with accurate molecular subtyping is critical for guiding treatment and improving patient outcomes. Traditional molecular subtyping via immuno-histochemistry (IHC) test is invasive, time-consuming, and may not fully represent tumor heterogeneity. This study proposes a non-invasive approach using digital mammography images and deep learning algorithm for classifying breast cancer molecular subtypes. Four pretrained models, including two Convolutional Neural Networks (MobileNet_V3_Large and VGG-16) and two Vision Transformers (ViT_B_16 and ViT_Base_Patch16_Clip_224) were fine-tuned to classify images into HER2-enriched, Luminal, Normal-like, and Triple Negative subtypes. Hyperparameter tuning,… More >

Seyong Jin¹, Muhammad Fayaz², L. Minh Dang³, Hyoung-Kyu Song³, Hyeonjoon Moon^2,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-23, 2026, DOI:10.32604/cmc.2025.070667 - 10 November 2025

Abstract Brain tumors require precise segmentation for diagnosis and treatment plans due to their complex morphology and heterogeneous characteristics. While MRI-based automatic brain tumor segmentation technology reduces the burden on medical staff and provides quantitative information, existing methodologies and recent models still struggle to accurately capture and classify the fine boundaries and diverse morphologies of tumors. In order to address these challenges and maximize the performance of brain tumor segmentation, this research introduces a novel SwinUNETR-based model by integrating a new decoder block, the Hierarchical Channel-wise Attention Decoder (HCAD), into a powerful SwinUNETR encoder. The HCAD… More >

Arvind Mukundan^1,2, Riya Karmakar¹, Devansh Gupta³, Hsiang-Chen Wang^1,4,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-23, 2026, DOI:10.32604/cmc.2025.069646 - 10 November 2025

Abstract Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0. Manual inspection of products on assembly lines remains inefficient, prone to errors and lacks consistency, emphasizing the need for a reliable and automated inspection system. Leveraging both object detection and image segmentation approaches, this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning (DL) models. Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images… More >

Şeref Barbaros Arik^1,2,*, İnanç Güvenç^1,2

Canadian Journal of Urology, Vol.32, No.6, pp. 569-578, 2025, DOI:10.32604/cju.2025.068094 - 30 December 2025

Abstract Objectives: Differentiating benign from malignant testicular lesions is essential to avoid unnecessary surgery and ensure timely intervention. While conventional ultrasound remains the first-line imaging method, elastography and MRI provide additional functional and structural information. This study assesses the diagnostic utility of testicular elastography and magnetic resonance imaging (MRI) in differentiating benign and malignant testicular lesions. Methods: Patients with sonographically detected testicular masses were retrospectively evaluated using elastography, scrotal MRI, and tumor markers. Quantitative and qualitative imaging findings, lesion size, and laboratory values were recorded. Statistical analyses included Fisher’s exact test, logistic regression, Receiver operating characteristic… More >

Roland Mangold, Timea Teglas^*

BIOCELL, Vol.49, No.12, pp. 2239-2244, 2025, DOI:10.32604/biocell.2025.069925 - 24 December 2025

Abstract The quality of life in older adulthood is greatly influenced by cognitive aging, which in turn is affected by nutrition, especially as it relates to hippocampal function. Although the link between hippocampal function and nutrition is defined, the exact mechanics are still unknown. The commentary addresses how docosahexaenoic acid (DHA) contributes to age-related cognitive decline and may play a role in promoting neurogenesis and neuroplasticity on the molecular level. The current challenge to our understanding is to investigate how DHA influences hippocampal function and cognitive aging, which would be possible and even more detailed with More >

Maryam^1,*, Rahayu Puji², Luthfi Muhammad Zulfikar², Ikhsandy Ferry², Nadiyah Khairun¹, Hidayat³, Ilyas Rushdan Ahmad⁴, Syafri Edi⁵

Journal of Renewable Materials, Vol.13, No.12, pp. 2431-2451, 2025, DOI:10.32604/jrm.2025.02024-0063 - 23 December 2025

Abstract The development of the bioplastics industry addresses critical issues such as environmental pollution and food safety concerns. However, the industrialization of bioplastics remains underdeveloped due to challenges such as high production costs and suboptimal material characteristics. To enhance these characteristics, this study investigates bioplastics reinforced with Nanocrystalline Cellulose (NCC) derived from Oil Palm Empty Fruit Bunches (OPEFB), incorporating dispersing agents. The research employs a Central Composite Design from the Response Surface Methodology (RSM) with two factors: the type of dispersing agent (KCl and NaCl) and the NCC concentration from OPEFB (1%–5%), along with the dispersing… More >