Minyan Zhan¹, Wei Yang^2,3, Minghao Wu^4,*, Hsin-Yi Wang⁵, Yu-Hsien Ho⁵

Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.077926 - 18 May 2026

Abstract The inclination of wooden columns is a key indicator for evaluating the structural safety of traditional timber buildings in China. However, accurate measurement is challenging because these columns typically exhibit natural tapering, with diameters decreasing from the base to the top, and surface irregularities such as artificial cuts, cracks, and knots. Both the intrinsic geometric characteristics and surface defects reduce the precision of coordinate acquisition and the reliability of inclination estimation. To overcome these limitations, this study proposes a novel inclination measurement method for wooden columns in traditional timber buildings based on multi-section measurement and… More >

Mosammat Jannatul Kobra¹, Muhammad Rashid Majeed^2,*, Md Owahedur Rahman¹

Journal of Blockchain and Intelligent Computing, Vol.2, pp. 27-44, 2026, DOI:10.32604/jbic.2026.081492 - 13 May 2026

Abstract The proposed study introduces a blockchain-based framework for an adaptive security solution with real-time incident response and usability feedback for non-expert users. Traditional security solutions are often designed with static, opaque policies, which makes them complex. These issues make them less effective in dealing with complex environments. Thus, to make them more effective, the proposed framework introduces supervised machine learning for attack classification, unsupervised machine learning for anomaly detection, a risk-aware, adaptive policy engine, and a lightweight, tamper-evident, hash-linked ledger for auditable decision-making. The proposed framework uses a Random Forest classifier for BENIGN/ATTACK classification, and… More >

Soukaina Mjahed¹, Ouail Mjahed^2,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.081953 - 08 May 2026

Abstract The rapid emergence of sophisticated, dynamic, and rare or previously unseen attack pattern exposes fundamental limitations of conventional intrusion detection systems (IDS) based on static learning architectures. While deep learning (DL) models have demonstrated strong performance by capturing complex spatial and temporal traffic patterns, existing DL-based IDS largely rely on fixed decision structures, restricting adaptability to evolving threats. Furthermore, current hybrid DL-metaheuristic approaches typically use such metaheuristics as offline or auxiliary optimizers, without interacting with the deep model’s internal latent representations. This paper introduces a novel co-evolutionary IDS that establishes a tight, bidirectional coupling between… More >

Mengqi Liu, Haiqing Yao^*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.078181 - 08 May 2026

Abstract For the wide-coverage application scenarios, wireless rechargeable sensor networks are normally divided into multiple clusters to support the diversity and flexibility for monitoring, and use the mobile charger (MC) to support the sustainable charging of the network. Many efforts focus on optimizing the cluster head selection and mobile charger scheduling to improve the network energy efficiency and reliability. However, the existing work tends to use fixed triggering mechanism for cluster head (CH) rotation, and may trigger the rotation either too early or too late. Besides, the existing charging triggering mechanisms cannot track the changes in… More >

Akmalbek Abdusalomov¹, Mukhriddin Mukhiddinov^2,3, Kamola Abdurashidova², Alpamis Kutlimuratov⁴, Avazjon Marakhimov⁵, Kuanishbay Seytnazarov⁶, Young-Im Cho^1,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.077057 - 08 May 2026

Abstract Human emotions are intricate and difficult to decipher through various modalities. Current methodologies frequently employ inflexible fusion strategies that do not consider the dynamic and context-sensitive characteristics of emotional expressions in both visual and textual mediums. This paper presents SYMPHONIA (Synchronizing Facial and Textual Modalities for Emotion Understanding), an innovative architecture engineered to capture and amalgamate emotional signals from facial expressions and language, attuned to contextual and modality interactions. There are two parts to SYMPHONIA: a Facial Emotion Branch that uses Vision Transformers and facial landmarks, and a Textual Emotion Branch that uses RoBERTa embeddings… More >

Wariyo Godana Arero¹, Yaqin Zhao¹, Mudasir Ahmad Wani², Pir Noman Ahmad³, Kashish Ara Shakil^4,*, Sadique Ahmad⁵, Sidrak Habtemariam Teredda⁶, Merhawit Berhane Teklu⁷, Longwen Wu^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.080279 - 27 April 2026

Abstract Lung cancer accounts for the highest number of cancer deaths globally, underscoring the urgent need for early and precise detection to enhance patient outcomes. While deep learning has made remarkable strides in analyzing medical images, current approaches face a fundamental challenge. They cannot adequately capture detailed local patterns and broader contextual relationships within lung Computed tomography (CT) scans. To address this limitation, we introduce AMVT-NMN (adaptive multi-scale vision transformer with neuromorphic memory networks), which combines three complementary mechanisms. The dynamic adaptive kernel networks component intelligently adjusts receptive field sizes based on input characteristics, enabling flexible… More >

Mustaqeem Khan¹, Ufaq Khan², Mamoun Awad¹, Nazar Zaki¹, Guiyoung Son³, Soonil Kwon^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.079697 - 27 April 2026

Abstract Knowledge distillation has shown impressive results in different fields, including detection, recognition, and generation. These models are excellent at tasks such as speech recognition, but they need to be shrunk down using adaptive knowledge distillation (AKD). The use of AKD can improve human-computer interactions and streamline data collection in the field of Speech Emotion Recognition (SER). This study presents a high-level approach that employs a novel adaptive knowledge distillation (AKD) with spatio-temporal transformers to acquire advanced semantic features from the input signal. This method uses an instance-by-instance correlation between the teacher and a student to determine the More >

Wei-Teng Chang¹, Ben-Jye Chang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.077118 - 27 April 2026

Abstract Some critical applications of emergency, Active Safe Driving (ASD), eV2X, and LEO communications require ultra-low delay and highly reliable transmission according to beyond 5G-Advanced (5G-A), 6G, and LEO specifications. Related studies proposed various scheduling algorithms in terms of single and multiple QoS requirements. However, these approaches tend to prioritize traditional QoS requirements while neglecting crucial considerations such as bearer costs and associated benefits. Moreover, most scheduling neglects the carrying cost according to the radio resource state and the bringing reward from different types of flows. Thus, this paper proposes a novel cost-based flow scheduling (eSCFS)… More >

K. Mithra^1,*, Prem Kumar Santhanam²

Journal of Intelligent Medicine and Healthcare, Vol.4, pp. 87-97, 2026, DOI:10.32604/jimh.2026.080288 - 24 April 2026

Abstract Background: Retinal fundus imaging is central to early diagnosis of sight-threatening conditions, including diabetic retinopathy, glaucoma, and retinal vein occlusion. Clinical utility is compromised by non-uniform illumination, motion blur, and low contrast—artefacts that reduce diagnostic accuracy. Effective image enhancement is a prerequisite for reliable computer-aided ophthalmic diagnosis. Methods: This paper proposes a two-stage enhancement pipeline combining luminosity correction via HSV colour space decomposition with Contrast Limited Adaptive Histogram Equalization (CLAHE) on the Value (V) channel. Validation is conducted on three publicly available benchmarks: DRIVE (40 images), STARE (20 images), and CHASEDB1 (28 images). Quantitative metrics… More >

Shu Zhou, Wenfeng Yang, Guoxing Wu^*, Xinming Jiang, Qingmiao Guo

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2025.072997 - 27 April 2026

Abstract The integration of high-penetration distributed photovoltaic (PV) systems in low-voltage (LV) distribution networks introduces significant challenges, including voltage violations, power quality degradation, and coordination difficulties among multiple distributed energy resources. Grid-forming converters with droop control offer autonomous voltage and frequency regulation capabilities, yet conventional fixed-parameter droop strategies perform poorly in resistance-dominant LV networks under variable PV generation conditions. This paper proposes an adaptive droop control method that dynamically adjusts control parameters to address these challenges. The proposed strategy incorporates three key innovations: (1) power-flow-aware adaptive voltage droop coefficients specifically designed for resistance-dominant networks, (2) a… More >