Laurence Desjardins^*

Oncologie, Vol.22, No.4, pp. 189-194, 2020, DOI:10.32604/oncologie.2020.012377

Abstract We describe the most frequent malignant intraocular tumors, conjunctival tumors and some lids and orbital tumors. Primary intraocular malignant tumors are retinoblastoma in children and uveal melanoma in adults. For uveal melanoma, the liver is the most frequent site of metastasis and this is why it is justified to prescribe liver ultrasonography every 6 months to these patients. Metastatic tumors can occur in the uvea and more frequently in the posterior part called the choroid. They are more frequent after breast cancer and lung cancer. Conjunctival tumors can be epithelial (benign papillomas and epidermoid carcinomas) or melanocytic (benign naevi and… More >

Yang Yang^1,*, Qian Zhao¹, Linna Ruan², Zhipeng Gao¹, Yonghua Huo³, Xuesong Qiu¹

Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 1139-1155, 2020, DOI:10.32604/iasc.2020.011705

Abstract In network anomaly detection, network traffic data are often imbalanced, that is, certain classes of network traffic data have a large sample data volume while other classes have few, resulting in reduced overall network traffic anomaly detection on a minority class of samples. For imbalanced data, researchers have proposed the use of oversampling techniques to balance data sets; in particular, an oversampling method called the SMOTE provides a simple and effective solution for balancing data sets. However, current oversampling methods suffer from the generation of noisy samples and poor information quality. Hence, this study proposes an oversampling method for imbalanced… More >

Ji Qian¹, Fang Liu^2,*, Donghui Li³, Xin Jin⁴, Feng Li⁴

Journal of Cyber Security, Vol.2, No.4, pp. 157-166, 2020, DOI:10.32604/jcs.2020.011169

Abstract Anomaly detection using KPI (Key Performance Indicator) is critical for Internet-based services to maintain high service availability. However, given the velocity, volume, and diversified nature of monitoring data, it is difficult to obtain enough labelled data to build an accurate anomaly detection model for using supervised machine leaning methods. In this paper, we propose an automatic and generic transfer learning strategy: Detecting anomalies on a new KPI by using pretrained model on existing selected labelled KPI. Our approach, called KADT (KPI Anomaly Detection based on Transfer Learning), integrates KPI clustering and model pretrained techniques. KPI clustering is used to obtain… More >

Lewis Nkenyereye¹, Bayu Adhi Tama², Sunghoon Lim^3,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2217-2227, 2021, DOI:10.32604/cmc.2020.012432

Abstract An anomaly-based intrusion detection system (A-IDS) provides a critical aspect in a modern computing infrastructure since new types of attacks can be discovered. It prevalently utilizes several machine learning algorithms (ML) for detecting and classifying network traffic. To date, lots of algorithms have been proposed to improve the detection performance of A-IDS, either using individual or ensemble learners. In particular, ensemble learners have shown remarkable performance over individual learners in many applications, including in cybersecurity domain. However, most existing works still suffer from unsatisfactory results due to improper ensemble design. The aim of this study is to emphasize the effectiveness… More >

Adnan¹, Umar Khan², Naveed Ahmed³, Syed Tauseef Mohyud-Din⁴, Ilyas Khan^5,*, Dumitru Baleanu^6,7,8, Kottakkaran Sooppy Nisar⁹

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1563-1576, 2021, DOI:10.32604/cmc.2020.012326

Abstract Thermal transport investigation in colloidal suspensions is taking a significant research direction. The applications of these fluids are found in various industries, engineering, aerodynamics, mechanical engineering and medical sciences etc. A huge amount of thermal transport is essential in the operation of various industrial production processes. It is a fact that conventional liquids have lower thermal transport characteristics as compared to colloidal suspensions. The colloidal suspensions have high thermal performance due to the thermophysical attributes of the nanoparticles and the host liquid. Therefore, researchers focused on the analysis of the heat transport in nanofluids under diverse circumstances. As such, the… More >

Nishit Savla¹, Raksha Anand², Soumya Pandit^2,*, Ram Prasad^3,*

Journal of Renewable Materials, Vol.8, No.12, pp. 1581-1605, 2020, DOI:10.32604/jrm.2020.011803

Abstract Microbial fuel cells (MFCs) are an attractive innovation at the nexus of energy and water security for the future. MFC utilizes electrochemically active microorganisms to oxidize biodegradable substrates and generate bioelectricity in a single step. The material of the anode plays a vital role in increasing the MFC’s power output. The anode in MFC can be upgraded using nanomaterials providing benefits of exceptional physicochemical properties. The nanomaterials in anode gives a high surface area, improved electron transfer promotes electroactive biofilm. Enhanced power output in terms of Direct current (DC) can be obtained as the consequence of improved microbe-electrode interaction. However,… More >

Yoann Perreux¹, Marie Alexandre Chaix², Anna Kamp³, François-Pierre Mongeon², Magali Pham², Loïc Boussel¹, Roland Henaine¹, Annie Dore², Blandine Mondésert², Sylvie Di-Filippo¹, Paul Khairy², Francis Bessiere^1,*

Congenital Heart Disease, Vol.15, No.6, pp. 473-482, 2020, DOI:10.32604/CHD.2020.013032

Abstract Sudden cardiac death and heart failure are well known long-term complications after atrial switch for D-transposition of the great arteries (D-TGA). Right systemic ventricular dysfunction is common and myocardial ischemia has been implicated as a putative mechanism for sudden death, with coronary anomalies prevalent in 30% of cases. We sought to assess an association between adverse events and coronary anomalies in patients with D-TGA and atrial switch surgery. An observational study was conducted in 3 tertiary centers (Montreal Heart Institute, Canada, Nationwide Children’s hospital, Chicago, USA and Hopital cardiologique Louis Pradel de Lyon, France). Adults with D-TGA and atrial switch… More >

Lianne M. Geerdink^1,2,*, Malindi van der Mheen^3,4, Gideon J. du Marchie Sarvaas⁵, Irene M. Kuipers⁶, Stefan Frerich⁷, Henriëtte ter Heide², Willem A. Helbing⁸, Zina Feijzic¹, Christian Schroer⁹, Chris L. de Korte¹⁰, Livia Kapusta^1,11, Chris M. Verhaak¹², Elisabeth M. W. J. Utens^3,4

Congenital Heart Disease, Vol.15, No.6, pp. 457-472, 2020, DOI:10.32604/CHD.2020.012994

Abstract Background: Due to the improved survival rates of children and adolescents with congenital heart disease (CHD), more attention is now being directed towards their health-related quality of life (HRQoL), emotional and behavioral problems. Ebstein anomaly (EA) is a rare CHD with a broad clinical spectrum. The aim of the current study is to evaluate self- and proxy-reported HRQoL and emotional and behavioral problems in children and adolescents with EA. Methods: In this cross-sectional, multicenter study, we included EA patients (aged 8–17 years), who underwent routine clinical assessments in Dutch university hospitals between May 2017 and March 2019. The Generic Pediatric… More >

Adel Assiri^*

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 767-778, 2021, DOI:10.32604/cmc.2020.013813

Abstract Anomaly classification based on network traffic features is an important task to monitor and detect network intrusion attacks. Network-based intrusion detection systems (NIDSs) using machine learning (ML) methods are effective tools for protecting network infrastructures and services from unpredictable and unseen attacks. Among several ML methods, random forest (RF) is a robust method that can be used in ML-based network intrusion detection solutions. However, the minimum number of instances for each split and the number of trees in the forest are two key parameters of RF that can affect classification accuracy. Therefore, optimal parameter selection is a real problem in… More >

Jiachen Li, Xianchao Jiang, Sim-eng Zhang, Jinyang Liu, Yajuan Zhang, Jun Yan, Shoujun Li, Qiang Wang^*

Congenital Heart Disease, Vol.15, No.5, pp. 387-397, 2020, DOI:10.32604/CHD.2020.013127

Abstract Background: Ebstein’s anomaly (EA) is a malformation of the tricuspid valve (TV) and myopathy of the right ventricle (RV). Surgery is now the main treatment for the defect. Objective: To summarize our surgical results and experience based on patients with EA who were under 7 years of age and treated with different surgical treatments. Design: Single-center cohort study of Ebstein’s anomaly. Setting: China. Participants: 80 patients under 7 years old who were diagnosed of EA and underwent different surgical treatments were consecutively enrolled in our research from January 2010 to December 2019. Results: The median age of the 80 patients… More >