Xiaolu Wang^1,2, Haoyu Sun¹, Aiguo Wang¹, Xin Xia^3,*

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.073991 - 27 January 2026

Abstract To address the issues of insufficient and imbalanced data samples in proton exchange membrane fuel cell (PEMFC) performance degradation prediction, this study proposes a data augmentation-based model to predict PEMFC performance degradation. Firstly, an improved generative adversarial network (IGAN) with adaptive gradient penalty coefficient is proposed to address the problems of excessively fast gradient descent and insufficient diversity of generated samples. Then, the IGAN is used to generate data with a distribution analogous to real data, thereby mitigating the insufficiency and imbalance of original PEMFC samples and providing the prediction model with training data rich More >

Fatemeh Ahmadi Abkenari^*, Melika Zandi, Shanmugapriya Gopalakrishnan

Journal of Cyber Security, Vol.8, pp. 93-109, 2026, DOI:10.32604/jcs.2026.074197 - 20 January 2026

Abstract Nowadays, cyberattacks are considered a significant threat not only to the reputation of organizations through the theft of customers’ data or reducing operational throughput, but also to their data ownership and the safety and security of their operations. In recent decades, machine learning techniques have been widely employed in cybersecurity research to detect various types of cyberattacks. In the domain of cybersecurity data, and especially in Trojan detection datasets, it is common for datasets to record multiple statistical measures for a single concept. We referred to them as SWMF features in this paper, which include… More >

Hafsa Sidaq¹, Lei Wang¹, Sghaier Guizani^2,*, Hussain Haider³, Ateeq Ur Rehman^4,*, Habib Hamam^5,6,7

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071254 - 12 January 2026

Abstract Numerous sectors, such as education, the IT sector, and corporate organizations, transitioned to virtual meetings after the COVID-19 crisis. Organizations now seek to assess participants’ fatigue levels in online meetings to remain competitive. Instructors cannot effectively monitor every individual in a virtual environment, which raises significant concerns about participant fatigue. Our proposed system monitors fatigue, identifying attentive and drowsy individuals throughout the online session. We leverage Dlib’s pre-trained facial landmark detector and focus on the eye landmarks only, offering a more detailed analysis for predicting eye opening and closing of the eyes, rather than focusing… More >

Salahudin Robo^1,2, Triyanna Widiyaningtyas^1,*, Wahyu Sakti Gunawan Irianto¹

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-19, 2026, DOI:10.32604/cmc.2025.073011 - 09 December 2025

Abstract Recommendation systems are an integral and indispensable part of every digital platform, as they can suggest content or items to users based on their respective needs. Collaborative filtering is a technique often used in various studies, which produces recommendations by analyzing similarities between users and items based on their behavior. Although often used, traditional collaborative filtering techniques still face the main challenge of sparsity. Sparsity problems occur when the data in the system is sparse, meaning that only a portion of users provide feedback on some items, resulting in inaccurate recommendations generated by the system.… More >

Dike Chen^1,2,3, Zhiyong Qin², Ji Zhang², Hongyuan Wang^1,2,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-17, 2026, DOI:10.32604/cmc.2025.072494 - 09 December 2025

Abstract To address the challenges of small target detection and significant scale variations in unmanned aerial vehicle (UAV) aerial imagery, which often lead to missed and false detections, we propose Multi-scale Feature Fusion YOLO (MFF-YOLO), an enhanced algorithm based on YOLOv8s. Our approach introduces a Multi-scale Feature Fusion Strategy (MFFS), comprising the Multiple Features C2f (MFC) module and the Scale Sequence Feature Fusion (SSFF) module, to improve feature integration across different network levels. This enables more effective capture of fine-grained details and sequential multi-scale features. Furthermore, we incorporate Inner-CIoU, an improved loss function that uses auxiliary More >

Rashid Jahangir^1,*, Nazik Alturki², Muhammad Asif Nauman³, Faiqa Hanif¹

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-20, 2026, DOI:10.32604/cmc.2025.071574 - 09 December 2025

Abstract Human activity recognition (HAR) is a method to predict human activities from sensor signals using machine learning (ML) techniques. HAR systems have several applications in various domains, including medicine, surveillance, behavioral monitoring, and posture analysis. Extraction of suitable information from sensor data is an important part of the HAR process to recognize activities accurately. Several research studies on HAR have utilized Mel frequency cepstral coefficients (MFCCs) because of their effectiveness in capturing the periodic pattern of sensor signals. However, existing MFCC-based approaches often fail to capture sufficient temporal variability, which limits their ability to distinguish… More >

Fatima Khan¹, Amna Khan¹, Tariq Ali², Tariq Shahzad³, Tehseen Mazhar^4,*, Sunawar Khan⁵, Muhammad Adnan Khan^6,*, Habib Hamam^7,8,9,10

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-27, 2026, DOI:10.32604/cmc.2025.068228 - 09 December 2025

Abstract The rise in noise and air pollution poses severe risks to human health and the environment. Industrial and vehicular emissions release harmful pollutants such as CO₂, SO₂, CO, CH₄, and noise, leading to significant environmental degradation. Monitoring and analyzing pollutant concentrations in real-time is crucial for mitigating these risks. However, existing systems often lack the capacity to monitor both indoor and outdoor environments effectively.This study presents a low-cost, IoT-based pollution detection system that integrates gas sensors (MQ-135 and MQ-4), a noise sensor (LM393), and a humidity sensor (DHT-22), all connected to a Node MCU (ESP8266) microcontroller. The… More >

Mussad Mohammed Al-Zahrani^*, Taher Maatallah

Frontiers in Heat and Mass Transfer, Vol.23, No.6, pp. 1883-1905, 2025, DOI:10.32604/fhmt.2025.074656 - 31 December 2025

Abstract Conventional concentrator photovoltaics (CPV) face a persistent trade-off between high efficiency and high cost, driven by expensive multi-junction solar cells and complex active cooling systems. This study presents a computational investigation of a novel Multi-Focal Pyramidal Array (MFPA)-based CPV system designed to overcome this limitation. The MFPA architecture employs a geometrically optimized pyramidal concentrator to distribute concentrated sunlight onto strategically placed, low-cost monocrystalline silicon cells, enabling high efficiency energy capture while passively managing thermal loads. Coupled optical thermal electrical simulations in COMSOL Multiphysics demonstrate a geometric concentration ratio of 120×, with system temperatures maintained below More >

Y.C. Rodríguez-Gómez¹, J. Serrano-Arellano^1,*, F.N. Demesa-López¹, J.M. Belman-Flores², J.F. Ituna-Yudonago³

Frontiers in Heat and Mass Transfer, Vol.23, No.6, pp. 2073-2107, 2025, DOI:10.32604/fhmt.2025.069564 - 31 December 2025

Abstract The Trombe Wall (TW) is a low-cost, passive heating system known for its high thermal efficiency, particularly in cold and temperate climates. Recent research has explored its adaptability to warm-dry climates with high thermal variability, such as those found in central Mexico. This study presents a dynamic simulation-based analysis of the TW’s thermal performance in a representative social housing unit located in Pachuca de Soto, Hidalgo. Two models were compared—one with a south-facing TW system and one without—to evaluate indoor thermal comfort throughout a full annual cycle. The simulations were conducted using OpenStudio and EnergyPlus,… More > Graphic Abstract

Si Qin, Shu Tang, Lijiao Xie, Jianbo Zhu, Jianguo Sun^*

Oncology Research, Vol.33, No.12, pp. 4145-4154, 2025, DOI:10.32604/or.2025.068300 - 27 November 2025

Abstract Background: Primary pulmonary lymphoepithelioma-like carcinoma (PPLELC) is a rare subtype of primary non-small cell lung cancer (NSCLC), with no established treatment guidelines. We present a case of a young female with PPLELC who achieved a pathological complete response (pCR) in both primary and metastatic lesions after receiving combined immunotherapy and radiotherapy. Case description: We present a 33-year-old female patient with stage IVa (cT2bN0M1b) PPLELC. As a first-line treatment, the patient received seven cycles of nab-paclitaxel combined with toripalimab (a PD-1 inhibitor) and achieved stable disease. This was followed by toripalimab maintenance therapy for nearly 30 months.… More >