Peipeng Yu¹, Zhihua Xia^{1, *}, Jianwei Fei¹, Sunil Kumar Jha^{1, 2}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 743-760, 2020, DOI:10.32604/cmc.2020.011391

Abstract Coronaviruses are a well-known family of viruses that can infect humans or animals. Recently, the new coronavirus (COVID-19) has spread worldwide. All countries in the world are working hard to control the coronavirus disease. However, many countries are faced with a lack of medical equipment and an insufficient number of medical personnel because of the limitations of the medical system, which leads to the mass spread of diseases. As a powerful tool, artificial intelligence (AI) has been successfully applied to solve various complex problems ranging from big data analysis to computer vision. In the process of epidemic control, many algorithms… More >

Yonghong Xie^{1, 3}, Liangyuan Hu^{1, 3}, Xingxing Chen^{2, 3}, Jim Feng⁴, Dezheng Zhang^{1, 3, *}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 481-494, 2020, DOI:10.32604/cmc.2020.010297

Abstract As one of the most valuable assets in China, traditional medicine has a long history and contains pieces of knowledge. The diagnosis and treatment of Traditional Chinese Medicine (TCM) has benefited from the natural language processing technology. This paper proposes a knowledge-based syndrome reasoning method in computerassisted diagnosis. This method is based on the established knowledge graph of TCM and this paper introduces the reinforcement learning algorithm to mine the hidden relationship among the entities and obtain the reasoning path. According to this reasoning path, we could infer the path from the symptoms to the syndrome and get all possibilities… More >

Suhas S. Aralikatti¹, K. N. Ravikumar¹, Hemantha Kumar^1,*, H. Shivananda Nayaka¹, V. Sugumaran²

Structural Durability & Health Monitoring, Vol.14, No.2, pp. 127-145, 2020, DOI:10.32604/sdhm.2020.07595

Abstract The state of cutting tool determines the quality of surface produced on the machined parts. A faulty tool produces poor surface, inaccurate geometry and non-economic production. Thus, it is necessary to monitor tool condition for a machining process to have superior quality and economic production. In the present study, fault classification of single point cutting tool for hard turning has been carried out by employing machine learning technique. Cutting force and vibration signals were acquired to monitor tool condition during machining. A set of four tooling conditions namely healthy, worn flank, broken insert and extended tool overhang have been considered… More >

Hitesh Agrawal^1,2, Oriana K. Wright³, Kathleen E. Carberry^1,4, S. Kristen Sexson Tejtel^1,2, Carlos M. Mery^1,5, Silvana Molossi^1,2

Congenital Heart Disease, Vol.12, No.6, pp. 721-725, 2017, DOI: 10.1111/chd.12473

Abstract Background: Long-term outcome data on patients with anomalous aortic origin of coronary arteries (AAOCA) is sparse and they are often managed in a nonuniform manner. There is subjective perception of anxiety and unmet needs in these patients and families.
Methods: An online survey of 13 questions was sent to 74 families of patients with AAOCA between May and October 2015. Descriptive statistics were performed.
Results: A total of 31 (47%) families responded. Of these, 27 expressed the need to interact with other patients/families with AAOCA. The majority were interested in either face-to-face meetings (77%) or online support groups (71%). Regarding… More >

Ian S. Rogers^1,2, Jennifer A. Tremmel¹, Ingela Schnittger¹

Congenital Heart Disease, Vol.12, No.5, pp. 619-623, 2017, DOI:10.1111/chd.12499

Abstract A myocardial bridge is a segment of a coronary artery that travels into the myocardium instead of the normal epicardial course. Although it is general perception that myocardial bridges are normal variants, patients with myocardial bridges can present with symptoms, such as exertional chest pain, that cannot be explained by a secondary etiology. Such patients may benefit from individualized medical/ surgical therapy. This article describes the prevalence, clinical presentation, classification, evaluation, and management of children and adults with symptomatic myocardial bridges. More >

William N. Evans^1,2, Ruben J. Acherman^1,2, Michael L. Ciccolo^1,3, Sergio A. Carrillo^1,3, Gary A. Mayman^1,2, Carlos F. Luna^1,2, Robert C. Rollins^1,2, William J. Castillo^1,2, Alvaro Galindo^1,2, Abraham Rothman^1,2, John A. Alexander^1,2, Tina W. Kwan^1,2, Humberto Restrepo^1,2

Congenital Heart Disease, Vol.12, No.5, pp. 583-587, 2017, DOI:10.1111/chd.12487

Abstract Objective: We hypothesized that a right aortic arch in situs solitus, with or without an associated cardiovascular malformation, is often associated with a vascular ring.
Methods: From those born in Southern Nevada between March 2012 and March 2017, we identified 50 (3.6 per 10,000 live births) with a right aortic arch and situs solitus. From the 50 patients, 6 did not meet inclusion criteria for further analysis.
Results: Of the 44 remaining, 33 (75%) had a vascular ring. Of the 33 with a vascular ring, 26 (79%) occurred with an isolated right aortic arch, and 7 (21%) had an associated… More >

Xiaoping Zhao^{1, 4}, Yifei Wang^{2, *}, Yonghong Zhang², Jiaxin Wu¹, Yunqing Shi³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 571-587, 2020, DOI:10.32604/cmc.2020.06363

Abstract Stochastic resonance can use noise to enhance weak signals, effectively reducing the effect of noise signals on feature extraction. In order to improve the early fault recognition rate of rolling bearings, and to overcome the shortcomings of lack of interaction in the selection of SR (Stochastic Resonance) method parameters and the lack of validation of the extracted features, an adaptive genetic random resonance early fault diagnosis method for rolling bearings was proposed. compared with the existing methods, the AGSR (Adaptive Genetic Stochastic Resonance) method uses genetic algorithms to optimize the system parameters, and further optimizes the parameters while considering the… More >

Heather Y. Sun¹, James A. Proudfoot², Rachel T. McCandless¹

Congenital Heart Disease, Vol.13, No.5, pp. 748-756, 2018, DOI:10.1111/chd.12648

Abstract Background: Fetal echocardiography can accurately diagnose critical congenital heart disease prenatally, but relies on referrals from abnormalities identified on routine obstetrical ultrasounds. Critical congenital heart disease that is frequently missed due to inadequate outflow tract imaging includes anomalies such as truncus arteriosus, double outlet right ventricle, transposition of the great arteries, tetralogy of Fallot, pulmonary stenosis, and aortic stenosis.
Objective: This study evaluated the prenatal detection rate of critical outflow tract anomalies in a single urban pediatric hospital before and after “AIUM Practice Guideline for the Performance of Obstetric Ultrasound Examinations,” which incorporated outflow tract imaging.
Design: Infants with outflow… More >

Xinyan Li¹, Xiaoxia Qiu¹, Huan Huang¹, Yili Zhao², Xueqin Li¹, Meng Li¹, Xiaoxian Tian¹

Congenital Heart Disease, Vol.13, No.2, pp. 282-287, 2018, DOI:10.1111/chd.12568

Abstract Objective: To evaluate the efficacy of using fetal heart size measurements derived from axial echocardiography to predict homozygous α-thalassemia-1.
Design: Prospective diagnostic study.
Setting: The carrier rate of α-thalassemia-1 (–/αα) in China’s Guangxi Zhuang Autonomous Region is approximately 15%. If both parents are carriers, the risk of homozygous a-thalassemia-1 in one pregnancy is 25%.
Patients: Singleton mid-pregnancies at risk of homozygous α-thalassemia-1 were enrolled.
Outcome Measures: Fetal heart measurements, including heart diameter (HD), heart length (HL), heart circumference (HC), and heart area (HA), were measured. The z-scores for these heart parameters were then calculated separately based on previously constructed z-score… More >

Kun Zhu¹, Shi Ying^{1, *}, Nana Zhang¹, Rui Wang¹, Yutong Wu¹, Gongjin Lan², Xu Wang²

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1161-1185, 2020, DOI:10.32604/cmc.2020.05247

Abstract SaaS software that provides services through cloud platform has been more widely used nowadays. However, when SaaS software is running, it will suffer from performance fault due to factors such as the software structural design or complex environments. It is a major challenge that how to diagnose software quickly and accurately when the performance fault occurs. For this challenge, we propose a novel performance fault diagnosis method for SaaS software based on GBDT (Gradient Boosting Decision Tree) algorithm. In particular, we leverage the monitoring mean to obtain the performance log and warning log when the SaaS software system runs, and… More >