Mahima Dahiya^*, Nitin Nitin

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4183-4201, 2023, DOI:10.32604/cmc.2023.032430 - 31 October 2022

Abstract Intrusion detection is critical to guaranteeing the safety of the data in the network. Even though, since Internet commerce has grown at a breakneck pace, network traffic kinds are rising daily, and network behavior characteristics are becoming increasingly complicated, posing significant hurdles to intrusion detection. The challenges in terms of false positives, false negatives, low detection accuracy, high running time, adversarial attacks, uncertain attacks, etc. lead to insecure Intrusion Detection System (IDS). To offset the existing challenge, the work has developed a secure Data Mining Intrusion detection system (DataMIDS) framework using Functional Perturbation (FP) feature… More >

Mohamed Abdel-Basset¹, Reda Mohamed¹, Ripon K. Chakrabortty², Michael J. Ryan², Yunyoung Nam^3,*, Mohamed Abouhawwash^4,5

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2883-2901, 2021, DOI:10.32604/cmc.2021.017854 - 24 August 2021

Abstract This paper proposes a new pre-processing technique to separate the most effective features from those that might deteriorate the performance of the machine learning classifiers in terms of computational costs and classification accuracy because of their irrelevance, redundancy, or less information; this pre-processing process is often known as feature selection. This technique is based on adopting a new optimization algorithm known as generalized normal distribution optimization (GNDO) supported by the conversion of the normal distribution to a binary one using the arctangent transfer function to convert the continuous values into binary values. Further, a novel… More >

Farouq Mohammad A. Alam¹, Sharifah Alrajhi¹, Mazen Nassar^1,2, Ahmed Z. Afify^3,*

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2185-2202, 2021, DOI:10.32604/cmc.2021.015089 - 05 February 2021

Abstract The main objective of this paper is to discuss a general family of distributions generated from the symmetrical arcsine distribution. The considered family includes various asymmetrical and symmetrical probability distributions as special cases. A particular case of a symmetrical probability distribution from this family is the Arcsine–Gaussian distribution. Key statistical properties of this distribution including quantile, mean residual life, order statistics and moments are derived. The Arcsine–Gaussian parameters are estimated using two classical estimation methods called moments and maximum likelihood methods. A simulation study which provides asymptotic distribution of all considered point estimators, 90% and… More >

Huifang Qian¹, Xuan Zhou^{1, *}, Mengmeng Zheng¹

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2153-2167, 2020, DOI:10.32604/cmc.2020.011843 - 16 September 2020

Abstract The core technology in an intelligent video surveillance system is that detecting and recognizing abnormal behaviors timely and accurately. The key breakthrough point in recognizing abnormal behaviors is how to obtain the effective features of the picture, so as to solve the problem of recognizing them. In response to this difficulty, this paper introduces an adjustable jump link coefficients model based on the residual network. The effective coefficients for each layer of the network can be set after using this model to further improving the recognition accuracy of abnormal behavior. A convolution kernel of 1×1… More >

Taicong Chen¹, Haitao Ma¹, Wei Gao²

CMES-Computer Modeling in Engineering & Sciences, Vol.87, No.3, pp. 239-270, 2012, DOI:10.3970/cmes.2012.087.239

Abstract Monte Carlo simulation method has been used extensively in probabilistic analyses of engineering systems and its popularity has been growing. While it is widely accepted that the simulation results are asymptotically accurate when the number of samples increases, certain exceptions do exist. The major objectives of this study are to reveal the conditions of the applicability of Monte Carlo method and to provide new insights into the accuracy of the simulation results in stochastic structural analysis. Firstly, a simple problem of a spring with random axial stiffness subject to a deterministic tension is investigated, using… More >

Ramamurty Raju P.¹, Rajesh S.¹, Satyanarayana B.², Ramji K.³

Structural Durability & Health Monitoring, Vol.7, No.1&2, pp. 139-152, 2011, DOI:10.3970/sdhm.2011.007.139

Abstract This paper presents the details of method of sample size determination to estimate the characteristic fatigue life of aluminum alloy, A356.2-T6. The characteristic fatigue life of the alloy has been estimated by assuming log normal distribution model. A step wise procedure is outlined to determine the number of specimens required at predetermined stress amplitude to estimate the fatigue life with an acceptable error at 50% probability and various confidence levels, 90%, 95% and 99%. Maximum percentage of errors has also been calculated for the above probability and confidence levels. Details of generation of S-N curve More >

P. Bocchini, C. Gentilini, F. Ubertini, E. Viola¹

Structural Durability & Health Monitoring, Vol.2, No.2, pp. 109-122, 2006, DOI:10.3970/sdhm.2006.002.109

Abstract This paper provides a simple and reliable method for the probabilistic characterization of the linear elastic response of frame structures with edge cracks of uncertain depth and location. A statistical analysis of the structural response allows consideration of the reliability of the investigated structure. A numerical example provides an indication of the performance of the approach proposed. More >