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 >

Jin Wang^{1, 2}, Wencheng Chen¹, Lei Wang^{3, *}, R. Simon Sherratt⁴, Osama Alfarraj⁵, Amr Tolba^{5, 6}

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2365-2384, 2020, DOI:10.32604/cmc.2020.011567

Abstract As the number of sensor network application scenarios continues to grow, the security problems inherent in this approach have become obstacles that hinder its wide application. However, it has attracted increasing attention from industry and academia. The blockchain is based on a distributed network and has the characteristics of nontampering and traceability of block data. It is thus naturally able to solve the security problems of the sensor networks. Accordingly, this paper first analyzes the security risks associated with data storage in the sensor networks, then proposes using blockchain technology to ensure that data storage in the sensor networks is… More >

Juan Li

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 35-48, 2019, DOI:10.31209/2018.100000003

Abstract K-Nearest Neighbor algorithm (KNN) is a simple and mature classification method. However there are susceptible factors influencing the classification performance, such as k value determination, the overlarge search space, unbalanced and multi-class patterns, etc. To deal with the above problems, a new classification algorithm that absorbs tree structure, tree pruning and adaptive k value method was proposed. The proposed algorithm can overcome the shortcoming of KNN, improve the performance of multi-class and unbalanced classification, reduce the scale of dataset maintaining the comparable classification accuracy. The simulations are conducted and the proposed algorithm is compared with several existing algorithms. The results… More >

Qigang Sun¹, Jian Wu¹, Dahai Wang^2,*, Yue Xiang², Haitao Liu¹, Xiaobin Sun³

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.1, pp. 287-302, 2020, DOI:10.32604/cmes.2020.09118

Abstract Downburst event is identified as a major cause to failure of transmission lines in non-coastal regions. In this paper, a novel nonlinear analytical frame for quasi-static buffeting responses of hinged and multi-span insulator-line systems are derived based on the theory of cable structure. The closed-form solutions are presented and applied to predict nonlinear response including displacements and other reactions of the system subjected to a moving downburst wind in a case study. Accuracy and efficiency of the derived analytical frame are validated via comparisons with results from finite element method. More >

Hui Li¹, Cailin Shi^{2, 3}, Xin Liu^{2, 3}, Aziguli Wulamu^{2, 3, *}, Alan Yang⁴

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 987-1004, 2020, DOI:10.32604/cmc.2020.09812

Abstract The difference in electricity and power usage time leads to an unbalanced current among the three phases in the power grid. The three-phase unbalanced is closely related to power planning and load distribution. When the unbalance occurs, the safe operation of the electrical equipment will be seriously jeopardized. This paper proposes a Hierarchical Temporal Memory (HTM)-based three-phase unbalance prediction model consisted by the encoder for binary coding, the spatial pooler for frequency pattern learning, the temporal pooler for pattern sequence learning, and the sparse distributed representations classifier for unbalance prediction. Following the feasibility of spatialtemporal streaming data analysis, we adopted… More >

SAIDA MELIANI¹, SOUMAYA TOUMI¹, HEYTHEM DJAHOUDI², KHALED DEGHDEGH³, KAMEL AMOURA⁴, ABDELGHANI DJAHOUDI^5,*

BIOCELL, Vol.44, No.2, pp. 175-182, 2020, DOI:10.32604/biocell.2020.09097

Abstract Objective: The aim of this study is to detect in vitro the synergetic activity of colistin in combination with imipenem, amikacin or ciprofloxacin, at sub-inhibitory concentrations, against carbapenems-resistant (CR) Acinetobacter baumannii and Pseudomonas aeruginosa strains isolated from various wards in Annaba teaching hospital in eastern Algeria.
Materials and Methods: The minimal inhibitory concentrations (MIC) were determined by broth macrodilution (BMD). Carbapenemase encoding genes were screened using polymerase chain reaction (PCR). The activity of colistin in combination with second antibiotic was evaluated by the Checkerboard Technique.
Results: 39 CR P. aeruginosa and 21 CR A. baumanni strains where collected. The MIC… More >

Jun Oyamada¹, Chisato Shimizu¹, Jihoon Kim², Matthew R. Williams^1,3, Eileen Png⁴, Martin L. Hibberd⁴, Adriana H. Tremoulet^1,3, James C. Perry^1,3, Jane C. Burns^1,3

Congenital Heart Disease, Vol.14, No.2, pp. 213-220, 2019, DOI:10.1111/chd.12696

Abstract Background: We previously described the association of genetic variants in calcium channel genes and susceptibility to Kawasaki disease (KD), an acute, self‐limited vas‐ culitis, and the most common cause of acquired cardiac disease in children. Abnormal repolarization of cardiomyocytes and changes in T wave morphology have been re‐ ported in KD but have not been studied systematically.
Methods: We analyzed acute and convalescent ECG T wave morphology in two inde‐ pendent cohorts of KD subjects and studied the association between bifid T waves and genetic variants in previously reported genes with SNVs associated with cardiac repolarization.
Results: Bifid T waves… More >

Salinas Jiménez V, JC Raya Pérez, CL Aguirre Mancilla, F Chablé Moreno, JG Ramírez Pimentel, G García Rodríguez, J Covarrubias Prieto

Phyton-International Journal of Experimental Botany, Vol.85, pp. 203-209, 2016, DOI:10.32604/phyton.2016.85.203

Abstract Eighty S1 maize (Zea mays L.) lines derived from halfsib families with good yield potential (greater than landraces in the region) were evaluated, with the purpose of selecting outstanding lines. Native populations are a source of germplasm for genetic improvement through selection and hybridization. Analysis of variance showed highly significant differences between the lines S1 in the variables days to anthesis (FM), silking date (FF), plant height (Apl), ear height (Amz), leaves above ear (NHEmz), ear length (Lmz), row number (Nhil), kernels per row (Ghil), total kernels per ear (TGmz) and grain yield (Rend). All variables showed high variability, an… More >

Hernández-Ibáñez L, J Sahagún-Castellanos, JE Rodríguez-Pérez, MG Peña-Ortega, LM Rodríguez-Martínez

Phyton-International Journal of Experimental Botany, Vol.83, pp. 311-318, 2014, DOI:10.32604/phyton.2014.83.311

Abstract In many countries, tomato (Solanum lycopersicum L.) is the most important horticultural species, but good variety seeds are expensive. In hybrid breeding, the number of possible single crosses is too large with only a few lines. With 60 lines, for example, 1770 single-cross hybrids can be formed. This makes it expensive and even impossible to conduct an adequate experimental evaluation. These cases require the availability of methods for predicting hybrid performance. This study was designed to evaluate a method to predict fruit yield in tomato hybrids based on genomic fingerprints, the theory of mixed models, and the experimental evaluation of… More >

Borghi ML¹, MA Ibañez¹, NC Bonamico¹, MV Kandus², D Almorza Gomar³, EA Guillin², JC Salerno², MA Di Renzo¹

Phyton-International Journal of Experimental Botany, Vol.81, pp. 123-131, 2012, DOI:10.32604/phyton.2012.81.123

Abstract Mal de Río Cuarto (MRC) disease is a significant threat to corn production in Argentina. Sixty six hybrid combinations derived from the cross of twelve flint maize (Zea mays L) inbred lines were evaluated using a completely randomized block design with two replications. MRC disease severity grade (SG) and grain yield (GY) were the analyzed traits. Our objectives were to estimate the general (GCA) and specific (SCA) combining abilities for these traits among twelve corn inbred lines, and to identify potential heterotic relationships among them. Diallel crosses were performed and these results were compared using Griffing’s method 2 model I… More >