John J. Araujo^1,2,*

Congenital Heart Disease, Vol.20, No.1, pp. 61-75, 2025, DOI:10.32604/chd.2025.062927 - 18 March 2025

Abstract Today, more than 90% of children who are born with congenital heart disease survive and reach adulthood, especially in developed countries. Consequently, the population of adults with congenital heart disease has increased significantly over the last few decades. In Latin America and the Caribbean countries, this same scenario is occurring at an accelerated pace. Loss to follow-up is a global problem in adults with congenital heart disease, ranging from 30–60%. In Latin America and Caribbean countries, it is estimated that less than 10% of adults with congenital heart disease are being followed. The small number More >

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 >

Prathap Sarma¹, Palesa Mogane^2,*, Katharina Vanderdonck³, Moses Kebalepile¹, Palesa Motshabi-Chakane⁴

Congenital Heart Disease, Vol.20, No.1, pp. 41-53, 2025, DOI:10.32604/chd.2025.060382 - 18 March 2025

Abstract Background: Congenital cardiac diseases (CCD) are common congenital birth defects that require high-risk surgery. Outcomes following congenital cardiac surgery in children living in high-income countries (HIC) have been documented, but little is known from the African continent. This study aimed to determine factors associated with perioperative mortality in patients who underwent congenital cardiac surgery at our institution. Methods: This retrospective, cross-sectional study was conducted at Charlotte Maxeke Johannesburg Academic Hospital over 12 years (2006–2017). A multivariable regression analysis was performed for the factors which had a p-value of 0.1 and less in the univariable regression analysis. A… More >

Ahmed M. Dardeer^1,2,3,#, Victoria M. Stoll^1,2,#, Boyang Liu^1,2, William E. Moody^1,2, Colin D. Chue¹, Paul Clift^1,2, Roman Wesolowski⁴, Lucy E. Hudsmith¹, Richard P. Steeds^1,2,*

Congenital Heart Disease, Vol.20, No.1, pp. 27-39, 2025, DOI:10.32604/chd.2025.059729 - 18 March 2025

Abstract Background: Patients with unrepaired Ebstein’s anomaly experience exercise intolerance, heart failure and premature mortality. Volumetric assessment of right ventricular function is difficult due to the complex anatomy of the right ventricle and tricuspid valve. Myocardial deformation indices are an early marker in other cardiac pathologies of ventricular dysfunction. Objectives: 1. Assess myocardial deformation in unrepaired Ebstein’s compared to healthy controls. 2. Investigate the relationships between myocardial deformation and exercise capacity. Methods: Myocardial deformation parameters (strain) were calculated using feature tracking from standard cardiac magnetic resonance cine images. Cardiopulmonary exercise results were included where available. Results: 36 patients… More >

Walter Timo de Vries^*, Veronica Cristina Astudillo Avila, Achmad Ghozali

Revue Internationale de Géomatique, Vol.34, pp. 125-149, 2025, DOI:10.32604/rig.2025.057970 - 11 March 2025

Abstract The development of Indonesia’s New Capital City (Ibu Kota Negara (IKN)) does not only offer opportunities but also faces uncertainties. One of these concerns is wastewater management, in terms of volume, location, and treatment facilities. To evaluate how the city might be able to manage this, this study starts with a theoretical evaluation of which wastewater management principles are crucial. Then the empirical study evaluates where and how the current infrastructure of the IKN could manage the wastewater and assesses—based on spatial scenarios—if the current wastewater management plans for the IKN are adequate. A Geographic… More >

Guodong Yuan^1,*, Jin Xie²

Journal on Artificial Intelligence, Vol.7, pp. 1-16, 2025, DOI:10.32604/jai.2025.061437 - 14 March 2025

Abstract This paper addresses the problem of access efficiency in multi-robot systems to the monitoring area. A distributed algorithm for multi-robot continuous monitoring, based on the uncertainty of target points, is used to minimize the uncertainty and instantaneous idle time of all target points in the task domain, while maintaining a certain access frequency to the entire task domain at regular time intervals. During monitoring, the robot uses shared information to evaluate the cumulative uncertainty and idle time of the target points, and combines the update list collected from adjacent target points with a utility function More >

Nataliya Shakhovska, Volodymyr Shymanskyi^*, Maksym Prymachenko

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4469-4484, 2025, DOI:10.32604/cmc.2025.062675 - 06 March 2025

Abstract Time series forecasting is important in the fields of finance, energy, and meteorology, but traditional methods often fail to cope with the complex nonlinear and nonstationary processes of real data. In this paper, we propose the FractalNet-LSTM model, which combines fractal convolutional units with recurrent long short-term memory (LSTM) layers to model time series efficiently. To test the effectiveness of the model, data with complex structures and patterns, in particular, with seasonal and cyclical effects, were used. To better demonstrate the obtained results and the formed conclusions, the model performance was shown on the datasets More >

Abdul Ahad^1,2, Ira Puspitasari^1,3,*, Jiangbin Zheng², Shamsher Ullah⁴, Farhan Ullah⁵, Sheikh Tahir Bakhsh⁶, Ivan Miguel Pires^7,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5115-5134, 2025, DOI:10.32604/cmc.2025.062605 - 06 March 2025

Abstract This research explores the use of Fuzzy K-Nearest Neighbor (F-KNN) and Artificial Neural Networks (ANN) for predicting heart stroke incidents, focusing on the impact of feature selection methods, specifically Chi-Square and Best First Search (BFS). The study demonstrates that BFS significantly enhances the performance of both classifiers. With BFS preprocessing, the ANN model achieved an impressive accuracy of 97.5%, precision and recall of 97.5%, and an Receiver Operating Characteristics (ROC) area of 97.9%, outperforming the Chi-Square-based ANN, which recorded an accuracy of 91.4%. Similarly, the F-KNN model with BFS achieved an accuracy of 96.3%, precision More >

Dae-Kyoo Kim^*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 3843-3872, 2025, DOI:10.32604/cmc.2025.062552 - 06 March 2025

Abstract Design patterns offer reusable solutions for common software issues, enhancing quality. The advent of generative large language models (LLMs) marks progress in software development, but their efficacy in applying design patterns is not fully assessed. The recent introduction of generative large language models (LLMs) like ChatGPT and CoPilot has demonstrated significant promise in software development. They assist with a variety of tasks including code generation, modeling, bug fixing, and testing, leading to enhanced efficiency and productivity. Although initial uses of these LLMs have had a positive effect on software development, their potential influence on the… More >

Huiyao Dong¹, Igor Kotenko^2,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4263-4285, 2025, DOI:10.32604/cmc.2025.062439 - 06 March 2025

Abstract The growing complexity of cyber threats requires innovative machine learning techniques, and image-based malware classification opens up new possibilities. Meanwhile, existing research has largely overlooked the impact of noise and obfuscation techniques commonly employed by malware authors to evade detection, and there is a critical gap in using noise simulation as a means of replicating real-world malware obfuscation techniques and adopting denoising framework to counteract these challenges. This study introduces an image denoising technique based on a U-Net combined with a GAN framework to address noise interference and obfuscation challenges in image-based malware analysis. The… More >