Shih-Lin Lin^*, Cheng-Wei Li

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-20, 2026, DOI:10.32604/cmc.2025.071915 - 09 December 2025

Abstract This study focuses on developing a deep learning model capable of recognizing vehicle brands and models, integrated with a law enforcement intelligence platform to overcome the limitations of existing license plate recognition techniques—particularly in handling counterfeit, obscured, or absent plates. The research first entailed collecting, annotating, and classifying images of various vehicle models, leveraging image processing and feature extraction methodologies to train the model on Microsoft Custom Vision. Experimental results indicate that, for most brands and models, the system achieves stable and relatively high performance in Precision, Recall, and Average Precision (AP). Furthermore, simulated tests… More >

Vinh Truong Hoang^1,*, Nghia Dinh¹, Viet-Tuan Le¹, Kiet Tran-Trung¹, Bay Nguyen Van¹, Kittikhun Meethongjan^2,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-40, 2026, DOI:10.32604/cmc.2025.068733 - 10 November 2025

Abstract The Financial Technology (FinTech) sector has witnessed rapid growth, resulting in increasingly complex and high-volume digital transactions. Although this expansion improves efficiency and accessibility, it also introduces significant vulnerabilities, including fraud, money laundering, and market manipulation. Traditional anomaly detection techniques often fail to capture the relational and dynamic characteristics of financial data. Graph Neural Networks (GNNs), capable of modeling intricate interdependencies among entities, have emerged as a powerful framework for detecting subtle and sophisticated anomalies. However, the high-dimensionality and inherent noise of FinTech datasets demand robust feature selection strategies to improve model scalability, performance, and More >

Bassel Weiss¹, Segundo Esteban^2,*, Matilde Santos³

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3387-3418, 2025, DOI:10.32604/cmes.2025.070070 - 30 September 2025

Abstract Anomaly detection in wind turbines involves emphasizing its ability to improve operational efficiency, reduce maintenance costs, extend their lifespan, and enhance reliability in the wind energy sector. This is particularly necessary in offshore wind, currently one of the most critical assets for achieving sustainable energy generation goals, due to the harsh marine environment and the difficulty of maintenance tasks. To address this problem, this work proposes a data-driven methodology for detecting power generation anomalies in offshore wind turbines, using normalized and linearized operational data. The proposed framework transforms heterogeneous wind speed and power measurements into… More > Graphic Abstract

Poria Moradi¹, Zahra Naghibifar^2,3, Armin Naghipour^1,*

Congenital Heart Disease, Vol.20, No.1, pp. 77-87, 2025, DOI:10.32604/chd.2025.061784 - 18 March 2025

Abstract Introduction: The occurrence of congenital anomalies is one of the serious challenges in the world. Therefore, identifying related factors to reduce it is of particular importance. This study aimed to determine the incidence and factors related to congenital anomalies. Methods: An epidemiology study was conducted on 1567 infants and their parents in Kermanshah, Iran. The required information was extracted from the files of mothers in health centers. The data collection tool was a researcher-made checklist of 39 questions. The data was statistically analyzed with the STATA version 14 software. Result: The incidence of congenital anomalies was 2.9%… More >

Ghazi A. Alshumrani^*

Congenital Heart Disease, Vol.19, No.2, pp. 197-206, 2024, DOI:10.32604/chd.2024.049401 - 16 May 2024

Abstract Objective: Coronary artery anatomical variations and anomalies are an important topic due to their potential clinical manifestations. This study aims to investigate the prevalence of coronary artery anatomical variations and anomalies in symptomatic patients with coronary computed tomography angiography (CCTA). Methods: This is a retrospective study that included all symptomatic patients who had CCTA in a tertiary care hospital in Saudi Arabia during a period of seven years. Results: The total number of included patients was 507 (60% males) with a mean age of 57.4 years. Approximately 41% had luminal stenoses, averaging 49.7%. The total number… More >

Birgitta Svensson^1,2,*, Petru Liuba^1,2, Anne Wennick³, Malin Berghammer^4,5

Congenital Heart Disease, Vol.18, No.3, pp. 349-359, 2023, DOI:10.32604/chd.2023.028391 - 09 June 2023

Abstract Background: Parents of children with complex right ventricular outflow tract (RVOT) anomalies are confronted with their child’s need for heart surgery early in life and repeated reoperations later on. Preoperative assessment needs to be performed whenever an indication for reoperation is suspected. The aim was to illuminate the experiences of parents of children diagnosed with RVOT anomalies, in particular, how they experience their child’s heart disease and everyday life during the assessment and after the decision on whether to perform a reoperation. Method: Individual interviews (n = 27) were conducted with nine parents on three occasions between… More >

A. L. Amutha¹, R. Annie Uthra^1,*, J. Preetha Roselyn², R. Golda Brunet³

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3387-3401, 2023, DOI:10.32604/csse.2023.029904 - 03 April 2023

Abstract The invention of Phasor Measurement Units (PMUs) produce synchronized phasor measurements with high resolution real time monitoring and control of power system in smart grids that make possible. PMUs are used in transmitting data to Phasor Data Concentrators (PDC) placed in control centers for monitoring purpose. A primary concern of system operators in control centers is maintaining safe and efficient operation of the power grid. This can be achieved by continuous monitoring of the PMU data that contains both normal and abnormal data. The normal data indicates the normal behavior of the grid whereas the… More >

Lilia Oreto^1,*, Giuseppe Mandraffino², Paolo Ciliberti³, Teresa P. Santangelo⁴, Placido Romeo⁵, Antonio Celona⁵, Placido Gitto¹, Lorenzo Galletti³, Fiore S. Iorio³, Alfredo Di Pino¹, Aurelio Secinaro⁴, Paolo Guccione³, Robert H. Anderson⁶, Salvatore Agati¹

Congenital Heart Disease, Vol.18, No.1, pp. 97-111, 2023, DOI:10.32604/chd.2022.023619 - 09 January 2023

Abstract Aims: Evidence is emerging that, in the setting of isomerism, the atrial and bronchial arrangement are not always concordant, nor are these patterns always harmonious with the arrangement of the abdominal organs. We aimed to evaluate the concordance between these features in a cohort of patients with cardiac malformations in the setting of known isomerism, seeking to determine whether it was feasible to assess complexity on this basis, in this regard taking note of the potential value of bronchial as opposed to appendage morphology. Methods and Results: We studied 78 patients known to have isomerism of the… More > Graphic Abstract

Dalel Ben Ismail¹, Hela Elmannai^2,*, Souham Meshoul², Mohamed Saber Naceur¹

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2219-2236, 2023, DOI:10.32604/iasc.2023.028944 - 19 July 2022

Abstract Imagery assessment is an efficient method for detecting craniofacial anomalies. A cephalometric landmark matching approach may help in orthodontic diagnosis, craniofacial growth assessment and treatment planning. Automatic landmark matching and anomalies detection helps face the manual labelling limitations and optimize preoperative planning of maxillofacial surgery. The aim of this study was to develop an accurate Cephalometric Landmark Matching method as well as an automatic system for anatomical anomalies classification. First, the Active Appearance Model (AAM) was used for the matching process. This process was achieved by the Ant Colony Optimization (ACO) algorithm enriched with proximity… More >

Haya Mesfer Alshahrani¹, Faisal S. Alsubaei², Taiseer Abdalla Elfadil Eisa³, Mohamed K. Nour⁴, Manar Ahmed Hamza^5,*, Abdelwahed Motwakel⁵, Abu Sarwar Zamani⁵, Ishfaq Yaseen⁵

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1557-1570, 2022, DOI:10.32604/cmc.2022.027135 - 18 May 2022

Abstract The increasing quantity of sensitive and personal data being gathered by data controllers has raised the security needs in the cloud environment. Cloud computing (CC) is used for storing as well as processing data. Therefore, security becomes important as the CC handles massive quantity of outsourced, and unprotected sensitive data for public access. This study introduces a novel chaotic chimp optimization with machine learning enabled information security (CCOML-IS) technique on cloud environment. The proposed CCOML-IS technique aims to accomplish maximum security in the CC environment by the identification of intrusions or anomalies in the network.… More >