WENBIAO CHEN, KEFAN BI, JINGJING JIANG, XUJUN ZHANG, HONGYAN DIAO^*

BIOCELL, Vol.45, No.4, pp. 885-899, 2021, DOI:10.32604/biocell.2021.012938 - 22 April 2021

Abstract The genome characteristics and structural functions of coding proteins correlate with the genetic diversity of the H1N1 virus, which aids in the understanding of its underlying pathogenic mechanism. In this study, analyses of the characteristic of the H1N1 virus infection-related genes, their biological functions, and infection-related reversal drugs were performed. Additionally, we used multi-dimensional bioinformatics analysis to identify the key genes and then used these to construct a diagnostic model for the H1N1 virus infection. There was a total of 169 differently expressed genes in the samples between 21 h before infection and 77 h… More >

Ibrahim B.M. Taha¹, Diaa-Eldin A. Mansour^2,*

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 739-752, 2021, DOI:10.32604/iasc.2021.017703 - 20 April 2021

Abstract Power transformer is one of the more important components of electrical power systems. The early detection of transformer faults increases the power system reliability. Dissolved gas analysis (DGA) is one of the most favorite approaches used for power transformer fault prediction due to its easiness and applicability for online diagnosis. However, the imbalanced, insufficient and overlap of DGA dataset impose a challenge towards powerful and accurate diagnosis. In this work, a novel fault diagnosis for power transformers is introduced based on DGA by using data transformation and six optimized machine learning (OML) methods. Four data… More >

Yudong Zhang^1,*, Qilong Wang², Sean H. Y. Yuan³

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.2, pp. 385-387, 2021, DOI:10.32604/cmes.2021.016386 - 19 April 2021

Abstract This article has no abstract. More >

Tapan Kumar Das¹, Pradeep Kumar Roy², Mohy Uddin³, Kathiravan Srinivasan¹, Chuan-Yu Chang^4,*, Shabbir Syed-Abdul⁵

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2413-2429, 2021, DOI:10.32604/cmc.2021.016698 - 13 April 2021

Abstract Machine learning based image analysis for predicting and diagnosing certain diseases has been entirely trustworthy and even as efficient as a domain expert’s inspection. However, the style of non-transparency functioning by a trained machine learning system poses a more significant impediment for seamless knowledge trajectory, clinical mapping, and delusion tracing. In this proposed study, a deep learning based framework that employs deep convolution neural network (Deep-CNN), by utilizing both clinical presentations and conventional magnetic resonance imaging (MRI) investigations, for diagnosing tumors is explored. This research aims to develop a model that can be used for… More >

Javaria Amin¹, Muhammad Sharif², Muhammad Almas Anjum³, Yunyoung Nam^4,*, Seifedine Kadry⁵, David Taniar⁶

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2451-2467, 2021, DOI:10.32604/cmc.2021.014199 - 13 April 2021

Abstract Coronavirus 19 (COVID-19) can cause severe pneumonia that may be fatal. Correct diagnosis is essential. Computed tomography (CT) usefully detects symptoms of COVID-19 infection. In this retrospective study, we present an improved framework for detection of COVID-19 infection on CT images; the steps include pre-processing, segmentation, feature extraction/fusion/selection, and classification. In the pre-processing phase, a Gabor wavelet filter is applied to enhance image intensities. A marker-based, watershed controlled approach with thresholding is used to isolate the lung region. In the segmentation phase, COVID-19 lesions are segmented using an encoder-/decoder-based deep learning model in which deepLabv3… More >

Elio Caruso^*, Silvia Farruggio, Salvatore Agati, Corrado Di Mambro

Congenital Heart Disease, Vol.16, No.4, pp. 309-331, 2021, DOI:10.32604/CHD.2021.015470 - 19 April 2021

Abstract Fetal arrhythmias reach up around 10% of the total third-level perinatal cardiology references. Sustained bradycardia is defined as a baseline fetal heart rate (FHR) of less than 110 bpm sustained for at least 10 min. The overall incidence of malignant fetal bradyarrhythmias, such as complete atrioventricular block (AVB) and channellopathies, is relatively rare, 1:5000 pregnancies, but represents a serious emergency for the gynecologist, neonatologists, and pediatric cardiologists. Fetal complete AVB is strongly associated with maternal connective tissue disease, but it can be also associated with congenital heart disease and usually with a poorer prognosis with More >

Xianqing Chen^1,2, Yan Yan^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 325-343, 2021, DOI:10.32604/cmes.2021.014489 - 30 March 2021

Abstract Alcoholism is an unhealthy lifestyle associated with alcohol dependence. Not only does drinking for a long time leads to poor mental health and loss of self-control, but alcohol seeps into the bloodstream and shortens the lifespan of the body’s internal organs. Alcoholics often think of alcohol as an everyday drink and see it as a way to reduce stress in their lives because they cannot see the damage in their bodies and they believe it does not affect their physical health. As their drinking increases, they become dependent on alcohol and it affects their daily More >

Afiqah Halim¹, Wan Azani Mustafa^1,2,*, Wan Khairunizam Wan Ahmad¹, Hasliza A. Rahim², Hamzah Sakeran³

Oncologie, Vol.23, No.1, pp. 73-88, 2021, DOI:10.32604/Oncologie.2021.015154 - 30 March 2021

Abstract Cervical cancer is a cell disease in the cervix that develops out of control in the female body. The cervix links the vagina (birth canal) with the upper section of the uterus, which can only be found in the female body. This is the second leading cause of death among women around the world. However, cervical cancer is currently one of the most preventable cancers if early detection is identified. The effect of unidentified cancer may increase the risk of death when the cell disease spreads to other parts of the female anatomy (metastasize). The… More >

Xian Ma¹, Tingyan Lv^2,*, Yingqiang Jin², Rongmin Chen², Dengxian Dong², Yingtao Jia²

Energy Engineering, Vol.118, No.3, pp. 691-705, 2021, DOI:10.32604/EE.2021.012701 - 22 March 2021

Abstract The large number of gas turbines in large power companies is difficult to manage. A large amount of the data from the generating units is not mined and utilized for fault analysis. This study focuses on F-class (9F.05) gas turbine generators and uses unsupervised learning and cloud computing technologies to analyse the faults for the gas turbines. Remote monitoring of the operational status are conducted. The study proposes a cloud computing service architecture for large gas turbine objects, which uses unsupervised learning models to monitor the operational state of the gas turbine. Faults such as More >

Sameh Abd ElGhany^1,2, Mai Ramadan Ibraheem³, Madallah Alruwaili⁴, Mohammed Elmogy^5,*

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 117-135, 2021, DOI:10.32604/cmc.2021.016102 - 22 March 2021

Abstract With the massive success of deep networks, there have been significant efforts to analyze cancer diseases, especially skin cancer. For this purpose, this work investigates the capability of deep networks in diagnosing a variety of dermoscopic lesion images. This paper aims to develop and fine-tune a deep learning architecture to diagnose different skin cancer grades based on dermatoscopic images. Fine-tuning is a powerful method to obtain enhanced classification results by the customized pre-trained network. Regularization, batch normalization, and hyperparameter optimization are performed for fine-tuning the proposed deep network. The proposed fine-tuned ResNet50 model successfully classified More >