Chaobin Wang^1,2, Xianghong Tang^1,2,*, Jianguang Lu^1,2, Jing Yang^1,2, Panliang Yuan^1,2

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.078998 - 08 May 2026

Abstract Mobile Edge Computing (MEC) facilitates the rapid response and energy-efficient execution of tasks on mobile devices. However, determining whether and where to offload tasks remains a significant challenge due to the constantly changing character of workloads in MEC environments. To address this issue, this paper proposes PreAlloc-A2C—a deep reinforcement learning actor-critic-based framework that calculates allocation scores by leveraging both task features (task size, required completion time, and waiting time) and server features (queue length and historical workload). This design enables fully distributed task offloading decisions without centralized coordination. Additionally, a Long Short-Term Memory (LSTM) network More >

Bing Xiong¹, Zhuoxiong Li¹, Yongqing Liu¹, Yu Tang¹, Jinyuan Zhao^2,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.078464 - 08 May 2026

Abstract Persistent Infrequent Flows (PIFs) refer to the packet flows that last for a long time but always at low frequencies in network traffic. Accurate identification of the PIFs plays a vital role in intrusion detection, attack prevention, traffic engineering, and other network fields. However, existing methods often require to save all flows for finding out the PIFs due to their infrequency feature, which brings about the problem of low identification accuracy and high memory overhead. To solve this problem, this paper proposes an accurate PIF identification method with low overhead called PIF-Identifier, composed of a… More >

Riyi Lin^*, Bi Pang, Xinwei Wang

Frontiers in Heat and Mass Transfer, Vol.24, No.2, 2026, DOI:10.32604/fhmt.2026.076874 - 30 April 2026

Abstract The thickening of condensed liquid film outside heat-exchange pipes and the pipe bundle effect can significantly degrade the heat transfer efficiency, thus restricting the vacuum phase-change heating furnace from achieving its rated thermal efficiency of over 90%. In this work, a heat transfer enhancement method coupling simple harmonic vibration with non-circular pipes was proposed. A CFD model describing the heat transfer process of horizontal pipes under vibratory conditions was established and stepwise validated against experimental data from published literature and the Nusselt analytical solution. Taking a 50 mm steel circular pipe as the reference, numerical… More >

Gürcan Durmaz^1,*, Gökhan Gürlek²

Frontiers in Heat and Mass Transfer, Vol.24, No.2, 2026, DOI:10.32604/fhmt.2026.075332 - 30 April 2026

Abstract This study examines the evolution of condenser technologies in household refrigerators, focusing on the potential for improving energy efficiency with hot-wall condensers (HWCs). Factors influencing this development, including refrigerant changes, consumer expectations, global regulations, and environmental factors, are evaluated. Design features, advantages, disadvantages, limitations, and comparisons with other condenser types are presented for HWCs. The review identifies key parameters affecting HWC performance: pipe diameter and pitch, outer surface material properties, adhesive tape properties, and contact resistances. The effects of environmental factors such as ambient temperatures and heat transfer coefficients are also considered. The results indicate… More > Graphic Abstract

Yan Shen¹, Lisheng Xie^2,*

International Journal of Mental Health Promotion, Vol.28, No.4, 2026, DOI:10.32604/ijmhp.2026.078186 - 28 April 2026

Abstract Objectives: Pediatric allergic rhinitis (AR) is a highly prevalent chronic inflammatory airway disease that significantly impairs children’s sleep, learning performance, and quality of life. Despite standardized pharmacotherapy, long-term symptom control remains suboptimal, which is related to the poor treatment compliance of patients and the insufficient disease awareness of parents. This study aimed to evaluate the effects of parental cognitive enhancement combined with parent–child psychological support on symptom control, the quality of life, and underlying intervention mechanisms in children aged 6–14 years with moderate to severe AR. Methods: A total of 150 children aged 6–14 years with… More >

Ovidijus Grigas^*, Rytis Maskeliūnas

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.077324 - 27 April 2026

Abstract Early detection of Mild Cognitive Impairment (MCI) with FDG-PET is essential for timely Alzheimer’s disease intervention. However, PET image quality is limited by low spatial resolution, partial volume effects, and Poisson noise. Standard enhancement methods, such as Bilateral filtering or Contrast Limited Adaptive Histogram Equalization (CLAHE), can increase contrast but often introduce heavy noise or distort image texture, while deep learning methods may produce hallucinated structures. We propose a fully data-adaptive, non-learned 3D enhancement framework whose output is deterministic for a given input volume, that combines Laplacian-based local contrast modulation with a gradient-gated Difference-of-Gaussians (DoG)… 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 >

Devita Amelia¹, R. A. Ilyas^1,2,*, Hairul Abral^2,3, Mochamad Asrofi⁴, Muhammad Asyraf Muhammad Rizal^2,5, Mohamad Zaki Hassan⁶, Mohamad Haafiz Mohamad Kassim^2,7,8, Nurul Fazita Mohammad Rawi^2,7,8, Nasrullah Razali⁹, Melbi Mahardika^2,7,8,10,*

Journal of Renewable Materials, Vol.14, No.4, 2026, DOI:10.32604/jrm.2025.02025-0147 - 24 April 2026

Abstract This study characterizes biocomposites derived from jicama starch and reinforced with microfibers obtained from jicama bagasse (JB). The incorporation of jicama bagasse microfibers into the jicama matrix was systematically varied at concentrations of 1, 2, 3, 4, and 5 wt%. The starch film and biocomposite were prepared using solution casting methodologies, employing glycerol as a plasticizing agent. The biocomposites were characterized using Fourier-transform infrared spectroscopy, X-ray diffraction analysis, and scanning electron microscopy. In addition, the moisture absorption and tensile properties were evaluated. The jicama starch contained 44% w/w amylose, whereas the jicama bagasse microfiber contained… More >

Taimoor Hassan¹, Ibrar Hussain^1,*, Hafiz Mahfooz Ul Haque², Hamid Turab Mirza³, Muhammad Nadeem Ali⁴, Byung-Seo Kim^4,*, Changheun Oh⁴

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.077510 - 09 April 2026

Abstract The expeditious proliferation of the smart computing paradigm has a remarkable upsurge towards Artificial Intelligence (AI) assistive reasoning with the incorporation of context-awareness. Context-awareness plays a significant role in fulfilling users’ needs whenever and wherever needed. Context-aware systems acquire contextual information from sensors/embedded sensors using smart gadgets and/or systems, perform reasoning using reinforcement learning (RL) or other reasoning techniques, and then adapt behavior. The core intention of using an RL-based reasoning strategy is to train agents to take the right actions at the right time and in the right place. Generally, agents are rewarded for… More >

Kiseok Kim^#, Taehoon Yoo^#, Sangmin Lee, Hwangnam Kim^*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.077415 - 09 April 2026

Abstract Conventional Low-Rank Adaptation (LoRA) constrains weight updates to a static linear low-rank manifold, which is inherently limited when applied to Reinforcement Learning (RL) tasks for Unmanned Aerial Vehicle (UAV) applications. UAVs operate in highly dynamic and nonstationary environments where rapid variations in sensing and state transitions lead to complex, nonlinear input–output relationships. Such environmental complexity cannot be adequately modeled by a static Low-rank approximation, making conventional LoRA approaches insufficient for the high-dimensional dynamics required in UAV applications. To overcome these limitations, we propose an attention-enhanced LoRA that constructs an input-dependent and intrinsically nonlinear adaptation manifold.… More >