Sanam Safi^1,2, Takato Yamasaki^1,3, David J. Glidden⁴, Stephen P. Sanders^1,5, Chrystalle Katte Carreon^1,6,*

Congenital Heart Disease, Vol.17, No.2, pp. 141-146, 2022, DOI:10.32604/chd.2022.019743

Abstract A maternally inherited 828 kb microdeletion of 2q37.3 manifested in a 3-week-old premature boy as left juxtaposition of the atrial appendages associated with tricuspid atresia, double outlet infundibulum, subvalvar pulmonary atresia, large secundum atrial septal defect, and right aortic arch with mirror-image branching, consistent with developmental arrest early in heart looping. To the best of our knowledge, no previous 2q37 deletion syndrome has been reported with such a severe cardiac dysmorphology. Hence, this case adds to the cardiac phenotypes identified in 2q37 deletion syndrome. More >

Hua Yan^1,2,3, Bo Song^1,3,*, Dongsheng Xu², Guodong Zhang²

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 199-217, 2022, DOI:10.32604/cmes.2022.016312

Abstract In this paper, three kinds of shear walls with full sleeve grouting, fully defective sleeve and partially defective are designed for finite element analysis to analyze the influence of defects on the seismic performance of shear walls. The research shows that at the beginning of loading (5 s), the three models begin to appear compressive damage at the bottom of the wall in all three models. The damage of the defect-free model develops rapidly, and the damage of the fully defective model is basically the same as that of the partially defective model. With the gradual increase of displacement control (15 s),… More >

Wuqin Tang, Qiang Yang, Wenjun Yan^*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1423-1439, 2022, DOI:10.32604/cmes.2022.018313

Abstract Defects detection with Electroluminescence (EL) image for photovoltaic (PV) module has become a standard test procedure during the process of production, installation, and operation of solar modules. There are some typical defects types, such as crack, finger interruption, that can be recognized with high accuracy. However, due to the complexity of EL images and the limitation of the dataset, it is hard to label all types of defects during the inspection process. The unknown or unlabeled create significant difficulties in the practical application of the automatic defects detection technique. To address the problem, we proposed an evolutionary algorithm combined with… More >

Zuhaira Muhammad Zain^1,*, Sapiah Sakri¹, Nurul Halimatul Asmak Ismail², Reza M. Parizi³

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1521-1546, 2022, DOI:10.32604/cmc.2022.022085

Abstract Developing successful software with no defects is one of the main goals of software projects. In order to provide a software project with the anticipated software quality, the prediction of software defects plays a vital role. Machine learning, and particularly deep learning, have been advocated for predicting software defects, however both suffer from inadequate accuracy, overfitting, and complicated structure. In this paper, we aim to address such issues in predicting software defects. We propose a novel structure of 1-Dimensional Convolutional Neural Network (1D-CNN), a deep learning architecture to extract useful knowledge, identifying and modelling the knowledge in the data sequence,… More >

Jakkrit Onshaunjit, Jakkree Srinonchat^*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 355-367, 2022, DOI:10.32604/cmc.2022.017698

Abstract An ideal printed circuit board (PCB) defect inspection system can detect defects and classify PCB defect types. Existing defect inspection technologies can identify defects but fail to classify all PCB defect types. This research thus proposes an algorithmic scheme that can detect and categorize all 14-known PCB defect types. In the proposed algorithmic scheme, fuzzy c-means clustering is used for image segmentation via image subtraction prior to defect detection. Arithmetic and logic operations, the circle hough transform (CHT), morphological reconstruction (MR), and connected component labeling (CCL) are used in defect classification. The algorithmic scheme achieves 100% defect detection and 99.05%… More >

Shi-Joon Yoo^1,2,*, Sanga Lee³, Regina de la Mora⁴, Ankavipar Saprungruang², Christoph Haller⁵, Lee N. Benson², Vladimiro Vida⁶, Alvise Guariento⁶, Christopher Z. Lam¹

Congenital Heart Disease, Vol.17, No.1, pp. 5-23, 2022, DOI:10.32604/CHD.2022.018728

Abstract Sinus venosus defects include two varieties, superior and inferior sinus venosus defects. The superior sinus venosus defect is characterized by abnormal communication between two closely related venoatrial structures: 1) the normally positioned superior vena cava-right atrium complex and 2) the right pulmonary vein-left atrium complex that is displaced leftward, forward and upward. Inferior sinus venosus defects primarily involve the inferior vena cava-right atrial junction while the right pulmonary vein-left atrial junction can also be affected. Because of the rarity and wide variation of the defects, the morphological characterization of sinus venosus defects is inconsistent among investigators and often inaccurate. Modern… More >

Taiki Haga^1,*, Tomoyuki Masuyama², Yoshiro Hayashi³, Takahiro Atsumi⁴, Kenzo Ishii⁵, Shinsuke Fujiwara⁶

Congenital Heart Disease, Vol.17, No.1, pp. 31-43, 2022, DOI:10.32604/CHD.2022.017407

Abstract Objectives: This study aimed to study the characteristics of in-hospital deterioration in patients with congenital heart disease who required rapid response system activation and identify risk factors associated with 1-month mortality. Methods: We retrospectively analysed data from a Japanese rapid response system registry with 35 participating hospitals. We included consecutive patients with congenital heart disease who required rapid response system activation between January 2014 and March 2018. Logistic regression analyses were performed to examine the associations between 1-month mortality and other patient-specific variables. Results: Among 9,607 patients for whom the rapid response system was activated, only 82 (0.9%) had congenital… More >

Adriano G. Passos, Tiago Cousseau, Marco A. Luersen^*

Computer Systems Science and Engineering, Vol.41, No.2, pp. 583-593, 2022, DOI:10.32604/csse.2022.020020

Abstract A proper detection and classification of defects in steel sheets in real time have become a requirement for manufacturing these products, largely used in many industrial sectors. However, computers used in the production line of small to medium size companies, in general, lack performance to attend real-time inspection with high processing demands. In this paper, a smart deep convolutional neural network for using in real-time surface inspection of steel rolling sheets is proposed. The architecture is based on the state-of-the-art SqueezeNet approach, which was originally developed for usage with autonomous vehicles. The main features of the proposed model are: small… More >

Mohammadrafie Khorgami¹, Ali Sadeghpour Tabaei^2,*, Elio Caruso^3,*, Silvia Farruggio³, Negar Omidi⁴, Maryam Moradian¹, Behzad Mohammadpour Ahranjani⁵, Zahra Khajali6 and Rahele Zamani¹

Congenital Heart Disease, Vol.16, No.6, pp. 573-584, 2021, DOI:10.32604/CHD.2021.016271

Abstract Background: Most children in need of cardiac pacemakers remain dependent on the function of the permanent from childhood to adulthood. We sought to evaluate and compare the function between epicardial and endocardial pacemakers in pediatric groups with different conditions. Methods: Between 2012 and 2018, this single-canter study evaluated 44 pediatric patients with indications for epicardial or endocardial pacemakers. Results: The 2 groups, at a median age of 5 (0.1–16) years, were compared concerning the characteristics of the leads used (n = 80: bipolar, unipolar, steroid-eluting, and non–steroid-eluting), survival data, and complications. The reason for pacemaker implantation was congenital complete heart… More >

Jacqueline S. Lee^1,2, Angelica Blais^1,2, Julia Jackson¹, Bhavika J. Patel¹, Lillian Lai⁴, Gary Goldfield^1,3, Renee Sananes⁵, Patricia E. Longmuir^1,2,3,*

Congenital Heart Disease, Vol.16, No.3, pp. 255-267, 2021, DOI:10.32604/CHD.2021.014628

Abstract Background: Pediatric cardiology patients often experience decreased quality of life (QoL) and higher rates of mental illness, particularly with severe disease, but the relationship between them and comparisons across diagnostic groups are limited. This mixed-methods cross-sectional study assessed the association between QoL anxiety and behavior problems among children with structural heart disease, arrhythmia, or other cardiac diagnoses. Methods: Children (6–14 years, n = 76, 50% female) and their parents completed measures of QoL (PedsQL), behavior (BASC-2, subset of 19 children) and anxiety (MASC-2, children 8+ years). Pearson correlations/regression models examined associations between QoL, behavior and anxiety, controlling for age, sex,… More >