Zahid Javid^1,2, Kush Lohana², Danial Murtaza², William Holderbaum^3,*

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.080073 - 18 June 2026

Abstract This paper introduces a novel hybrid method for Power System State Estimation (PS-SE) that effectively integrates the strengths of Weighted Least Squares (WLS) and the Extended Kalman Filter (EKF) through an adaptive weighting mechanism. The proposed method addresses key challenges in modern PS-SE, including measurement uncertainties, bad data detection and handling, and convergence reliability. By incorporating an adaptive weighting mechanism, the hybrid approach dynamically adjusts estimation parameters based on the quality of the measurements, enabling it to maintain high accuracy for clean data while demonstrating exceptional resilience against outliers and noisy measurements. The performance of… More >

Junyi Wang¹, Jianghai Geng^1,*, Jiaqi Liu², Haibin Zhu³

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.080895 - 15 June 2026

Abstract In intelligent manufacturing and remanufacturing systems, the thermal safety of the power distribution infrastructure is crucial for ensuring production continuity, equipment reliability, and operational resilience. Traditional temperature monitoring methods often have problems such as high deployment costs, strong environmental sensitivity, or limited physical interpretability in distributed workshop environments. To address these limitations, this study proposes a physically information-driven intelligent thermal color-changing fault identification framework. Based on thermochromic experiments, irreversible color-changing coatings are selected, which are combined with a visual-based computing pipeline for autonomous overheating detection. The framework proposes a thermal fault temperature identification algorithm based… More >

Hamza Ahmed¹, Hassan Jamil Syed^2,*, Aqsa Aslam¹, Sehar Zehra¹, Ummay Faseeha¹, Nurzati Iwani Othman²

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.080115 - 15 June 2026

Abstract Edge computing is an emerging model for latency-sensitive and distributed applications. However, the observability of edge computing systems in heterogeneous environments remains a challenge, as most existing approaches are limited to only the system, service, application, and network layers. This paper surveys state-of-the-art solutions for edge observability and monitoring. The paper further introduces a thematic taxonomy that groups the state-of-the-art edge observability and monitoring literature based on monitoring intent, telemetry indicators, observability scope, architectural layers, deployment environments, and observability toolchains. Finally, we compare representative solutions in terms of latency, system overhead, bandwidth consumption, and detection More >

Isam Bahaa Aldallal¹, Saadaldeen Rashid Ahmed^2,3, Abdullahi Abdu Ibrahim¹, Oguz Bayat⁴, Abu Saleh Musa Miah⁵, Fahmid Al Farid^6,7,*, Md. Hezerul Abdul Karim^6,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.078742 - 15 June 2026

Abstract Urban parking problems worsen traffic jams, gas use, and pollution. Old parking systems often lack up-to-date space information, which annoys drivers and wastes their time. This research presents a smart IoT-enabled real-time space monitoring and booking system applicable to both urban parking management and Smart Manufacturing logistics environments, including loading bay coordination and Automated Guided Vehicle (AGV) docking station management. The system employs ultrasonic and IR sensors, managed by an Arduino UNO, to identify vehicles and track space availability. A servo-motor regulates entry. Slot data is presented on a Liquid Crystal Display screen and accessible More >

Suranto^1,2, Rahmawaty^1,3,*, Isnen Fitri^1,4, Luthfi Hakim^1,3, Abdul Rauf^1,5, Delvian^1,3, Mehmet Cetin⁶, Ilknur Zeren Cetin⁶, Siti Aekbal Salleh^7,*

Revue Internationale de Géomatique, Vol.35, pp. 291-313, 2026, DOI:10.32604/rig.2026.081197 - 05 June 2026

Abstract Urban trees are a critical component of green infrastructure in tropical cities, yet city-scale evidence on tree health in Indonesia remains limited. This study assessed urban tree health in Medan City using the Forest Health Monitoring (FHM) protocol, Tree Level Index (TLI), GIS-based spatial analysis, and Normalized Difference Vegetation Index (NDVI) validation to support Eco Forest City planning. A total of 1184 trees, representing a 30% sample from 3947 inventoried trees across six sub-districts, were evaluated based on damage location, type, and severity. Average Nearest Neighbor (ANN) and Kernel Density Estimation (KDE) were applied to… More >

Chuanjiang Chen¹, Junyong Zhou^1,*, Binbin Du¹, Miaosi Dong^2,*, Liwen Zhang¹, Bitang Zhu³

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.081546 - 27 May 2026

Abstract Computer vision has been widely adopted in intelligent construction monitoring; however, existing studies primarily focus on identifying individual construction elements or isolated activities, with limited capability for integrated monitoring of complete construction workflows. Such workflow-level automation is a prerequisite for intelligent construction and unmanned job sites. To address the challenge of reliable visual recognition in drill-and-blast tunnel environments characterized by uneven illumination, localized glare, and dust interference, this study proposes a methodological framework for construction workflow recognition at the tunnel face using computer vision and context reasoning. The framework consists of three components: (1) a… More >

Kiran Deep Singh¹, Prabh Deep Singh², Narinder Kaur³, Jawad Khan^4,*, Dildar Hussain⁵, Yeong Hyeon Gu^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.080915 - 27 May 2026

Abstract In smart healthcare systems, Image data of critical patients is essential in controlling and diagnosing the disease development. To acquire the medical images, traditional methods encountered the difficulty of generating cost-effective data. This research work introduces a novel and innovative approach to collect high-quality image data from individuals with atypical clinical presentations. Initially, a new Internet of Medical Things (IoMT) image collection architecture is introduced. This design uses edge intelligence and motion-static synergy to make it easier to record both coarse-grained and fine-grained patient images. This study introduces an image acquisition technique that leverages edge… More >

Menahil Rahman¹, Waqas Ishtiaq², Amerah Alabrah^3,*, Arif Mehmood⁴, Rana Faraz Ahmed⁴, Iqra Khalid⁵, Farhan Amin^6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.078549 - 27 May 2026

Abstract Access to safe drinking water is a fundamental determinant of global health. The presence of contaminated water affects the citizens’ health. Per- and polyfluoroalkyl substances (PFAS) are often referred to as forever chemicals. They pose a persistent and growing threat to drinking water. In the literature, machine learning methods are used to identify the forever chemicals in water. However, traditional methods are not efficient and scalable. Thus, to solve this issue. This study develops a large-scale machine-learning framework for PFAS risk screening in US public water systems. The proposed framework incorporates data ingestion, preprocessing, and More >

Xinyu Yue¹, Zhenhua Li^1,2,*, Zhenxing Li¹, Tao Zhang¹, Yanchun Xu¹, Xiaozhen Zhao³

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2026.077395 - 27 May 2026

Abstract Winding deformation is a predominant cause of transformer failures and critically compromises the safe, reliable, and economic operation of power systems. To overcome the inadequacy of the conventional three-dimensional (3D) Lissajous curve method in discriminating among various types of winding faults, this paper proposes an online monitoring method for transformer winding deformation based on 3D Lissajous curves. In the proposed method, the primary current di1(t)/dt, the derivative of the primary current di1(t)/dt, and the voltage difference between the primary and secondary sides Δu(t) are adopted as the coordinate axes to construct 3D Lissajous… More >

Maher Kurdi^1,*, Amber Hassan², Bashar Reda³, Anas Nooh³, Mohammed Alsobaie⁴, Alaa Alkhotani⁵, Dahlia S. Mirdad⁶, Majid Almansouri⁷, Khalid Khashoggi⁸, Manal Halwani⁹, Motaz Fadul¹, Humaira Waseem^10,11, Siti S. Maidin¹⁰, Muhammed Imtiaz Farid¹²

Oncology Research, Vol.34, No.6, 2026, DOI:10.32604/or.2026.078833 - 21 May 2026

Abstract Background: Pediatric sarcomas are aggressive malignancies characterized by marked biological heterogeneity and a high risk of relapse. Standard surveillance relies on imaging and invasive biopsies, which may fail to detect early molecular disease. Liquid biopsy using circulating tumor DNA (ctDNA) and microRNAs offers a minimally invasive strategy for longitudinal monitoring. This study aimed to evaluate dynamic changes in ctDNA and circulating microRNAs during treatment and examined their associations with treatment response, disease recurrence, and survival outcomes. Methods: This prospective cohort study included 100 pediatric patients with histologically confirmed sarcomas. Serial peripheral blood samples were collected at… More >