Lei Hu^1,2,#, Meng Chen^2,3,#, Haiming Dai^2,3,4, Hongzhi Wang^2,3,4,*, Wulin Yang^2,3,4,*

Oncologie, Vol.24, No.4, pp. 803-822, 2022, DOI:10.32604/oncologie.2022.026419

Abstract Background and Aim: Hundreds of consistently altered metabolic genes have been identified in breast cancer (BC), but their prognostic value remains to be explored. Therefore, we aimed to build a prediction model based on metabolism-related genes (MRGs) to guide BC prognosis. Methods: Current work focuses on constructing a novel MRGs signature to predict the prognosis of BC patients using MRGs derived from the Virtual Metabolic Human (VMH) database, and expression profiles and clinicopathological data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Results: The 3-MRGs-signature constructed by SERPINA1, QPRT and PXDNL was found to be an… More >

S. Sudha^*, A. Srinivasan, T. Gayathri Devi

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1985-2000, 2023, DOI:10.32604/csse.2023.030960

Abstract The substantial vision loss due to Diabetic Retinopathy (DR) mainly damages the blood vessels of the retina. These feature changes in the blood vessels fail to exist any manifestation in the eye at its initial stage, if this problem doesn’t exhibit initially, that leads to permanent blindness. So, this type of disorder can be only screened and identified through the processing of fundus images. The different stages in DR are Micro aneurysms (Ma), Hemorrhages (HE), and Exudates, and the stages in lesion show the chance of DR. For the advancement of early detection of DR in the eye we have… More >

Wael Alosaimi^1,*, M. Irfan Uddin²

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1387-1401, 2022, DOI:10.32604/cmes.2022.018433

Abstract Deep Learning (DL) techniques as a subfield of data science are getting overwhelming attention mainly because of their ability to understand the underlying pattern of data in making classifications. These techniques require a considerable amount of data to efficiently train the DL models. Generally, when the data size is larger, the DL models perform better. However, it is not possible to have a considerable amount of data in different domains such as healthcare. In healthcare, it is impossible to have a substantial amount of data to solve medical problems using Artificial Intelligence, mainly due to ethical issues and the privacy… More >

Sanaa Al-Marzouki¹, Farrukh Jamal², Christophe Chesneau^3,*, Mohammed Elgarhy⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 437-458, 2020, DOI:10.32604/cmes.2020.011521

Abstract Recent studies have pointed out the potential of the odd Fréchet family (or class) of continuous distributions in fitting data of all kinds. In this article, we propose an extension of this family through the so-called “Topp-Leone strategy”, aiming to improve its overall flexibility by adding a shape parameter. The main objective is to offer original distributions with modifiable properties, from which adaptive and pliant statistical models can be derived. For the new family, these aspects are illustrated by the means of comprehensive mathematical and numerical results. In particular, we emphasize a special distribution with three parameters based on the… More >

Alberto Fernández Oliva¹, Francisco Maciá Pérez², José Vicente Berná-Martinez^2,*, Miguel Abreu Ortega³

Computer Systems Science and Engineering, Vol.34, No.3, pp. 131-144, 2019, DOI:10.32604/csse.2019.34.131

Abstract This study presents a method for the detection of outliers based on the Variable Precision Rough Set Model (VPRSM). The basis of this model is the generalisation of the standard concept of a set inclusion relation on which the Rough Set Basic Model (RSBM) is based. The primary contribution of this study is the improvement in detection quality, which is achieved due to the generalisation allowed by the classification system that allows a certain degree of uncertainty. From this method, a computationally efficient algorithm is proposed. The experiments performed with a real scenario and a comparison of the results with… More >

Kiranbir Kaur^{1, *}, Sandeep Sharma¹, Karanjeet Singh Kahlon²

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1625-1647, 2020, DOI:10.32604/cmc.2020.011535

Abstract Vendor lock-in can occur at any layer of the cloud stack-Infrastructure, Platform, and Software-as-a-service. This paper covers the vendor lock-in issue at Platform as a Service (PaaS) level where applications can be created, deployed, and managed without worrying about the underlying infrastructure. These applications and their persisted data on one PaaS provider are not easy to port to another provider. To overcome this issue, we propose a middleware to abstract and make the database services as cloud-agnostic. The middleware supports several SQL and NoSQL data stores that can be hosted and ported among disparate PaaS providers. It facilitates the developers… More >

Vanessa Marie Hormaza¹, Mark Conaway², Daniel Scott Schneider¹, Jeffrey Eric Vergales¹

Congenital Heart Disease, Vol.14, No.2, pp. 274-279, 2019, DOI:10.1111/chd.12722

Abstract Objective: Limited information is known on how right ventricular function affects outcomes after stage 2 palliation. We evaluated the impact of different right ventricular indices prior to stage 2 palliation on morbidity and mortality.
Design: Retrospective study design.
Setting: Pediatric Heart Network Single Ventricle Reconstruction Trial Public Data Set.
Patient: Any variant of stage 1 palliation and all anatomic hypoplastic left heart syndrome variants in the trial were evaluated. Echocardiograms prior to stage 2 palliation were analyzed and compared between those who failed and those who survived.
Intervention: None.
Outcome measures: Mortality was defined as death, listed for transplant, or… More >

Roberto Bellas^{1, *}, Javier Martínez¹, Ignacio Rivera², Ramón Touza², Miguel Gómez¹, Rafael Carreño¹

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.3, pp. 971-995, 2020, DOI:10.32604/cmes.2020.07530

Abstract The study of emergency evacuation in public spaces, buildings and large ships may present parallel characteristic in terms of complexity of the layout but there are also significant differences that can hindering passengers to reach muster stations or the lifeboats. There are many hazards on a ship that can cause an emergency evacuation, the most severe result in loss of lives. Providing safe and effective evacuation of passengers from ships in an emergency situation becomes critical. Recently, computer simulation has become an indispensable technology in various fields, among them, the evacuation models that recently evolved incorporating human behavioral factors. In… More >

R. Moskovic¹, P. E. J. Flewitt^1,2

Structural Durability & Health Monitoring, Vol.1, No.1, pp. 83-94, 2005, DOI:10.3970/sdhm.2005.001.083

Abstract Consideration of the structural integrity is one of the inputs when evaluating potential solutions to plant problems. Structural integrity assessments of components forming the pressure boundaries of nuclear plant evaluate safety margins against cleavage fracture. These assessments consider the reserve factors between the applied stress and fracture toughness of the material as well as temperature margins between the operating temperature and the temperature at which the steel is ductile as defined by upper shelf behaviour. To carry out these structural integrity assessments, estimates of cleavage fracture toughness are required. The approach presented in this paper allows for differences between cleavage… More >

Ling Tan^1,*, Chong Li², Jingming Xia², Jun Cao³

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 275-288, 2019, DOI:10.32604/cmc.2019.03735

Abstract Due to the widespread use of the Internet, customer information is vulnerable to computer systems attack, which brings urgent need for the intrusion detection technology. Recently, network intrusion detection has been one of the most important technologies in network security detection. The accuracy of network intrusion detection has reached higher accuracy so far. However, these methods have very low efficiency in network intrusion detection, even the most popular SOM neural network method. In this paper, an efficient and fast network intrusion detection method was proposed. Firstly, the fundamental of the two different methods are introduced respectively. Then, the self-organizing feature… More >