In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to detect IDS attacks with 98.80% accuracy when validated using UNSW-NB15 dataset. The experimental results show the proposed method presents satisfactory results when compared with those obtained in this field.
Vapor-liquid equilibrium data are presented for the binary systems n-hexane - 1-propanol, benzene - 1-propanol and n-hexane – benzene at 760 mm of mercury pressure. In addition ternary data are presented at selected compositions with respect to the 1-propanol in the 1-propanol, benzene, n-hexane system at 760 mmHg. The results indicate the relative volatility of n-hexane relative to benzene increases appreciably with addition of 1-propanol.
This study aims to show, the strength of steel beam-concrete slab system without using shear connectors (known as a non-composite action), where the effect of the friction force between the concrete slab and the steel beam has been investigated, by using finite element simulation.
The proposed finite element model has been verified based on comparison with an experimental work. Then, the model was adopted to study the system strength with a different steel beam and concrete slab profile. ABAQUS has been adopted in the preparation of all numerical models for this study.
After validation of the numerical models, a parametric study was conducted, with linear and non-linear Regression analysis. An equation re
... Show MoreAssessing water quality provides a scientific foundation for the development and management of water resources. The objective of the research is to evaluate the impact treated effluent from North Rustumiyia wastewater treatment plant (WWTP) on the quality of Diyala river. The model of the artificial neural network (ANN) and factor analysis (FA) based on Nemerow pollution index (NPI). To define important water quality parameters for North Al-Rustumiyia for the line(F2), the Nemerow Pollution Index was introduced. The most important parameters of assessment of water variation quality of wastewater were the parameter used in the model: biochemical oxygen demand (BOD), chemical oxygen dem
Active worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.
In this paper, an intelligent tracking control system of both single- and double-axis Piezoelectric Micropositioner stage is designed using Genetic Algorithms (GAs) method for the optimal Proportional-Integral-Derivative (PID) controller tuning parameters. The (GA)-based PID control design approach is a methodology to tune a (PID) controller in an optimal control sense with respect to specified objective function. By using the (GA)-based PID control approach, the high-performance trajectory tracking responses of the Piezoelectric Micropositioner stage can be obtained. The (GA) code was built and the simulation results were obtained using MATLAB environment. The Piezoelectric Micropositioner simulation model with th
... Show MoreLearning the vocabulary of a language has great impact on acquiring that language. Many scholars in the field of language learning emphasize the importance of vocabulary as part of the learner's communicative competence, considering it the heart of language. One of the best methods of learning vocabulary is to focus on those words of high frequency. The present article is a corpus based approach to the study of vocabulary whereby the research data are analyzed quantitatively using the software program "AntWordprofiler". This program analyses new input research data in terms of already stored reliable corpora. The aim of this article is to find out whether the vocabularies used in the English textbook for Intermediate Schools in Iraq are con
... Show MoreIn this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de
... Show MorePower-electronic converters are essential elements for the effective interconnection of renewable energy sources to the power grid, as well as to include energy storage units, vehicle charging stations, microgrids, etc. Converter models that provide an accurate representation of their wideband operation and interconnection with other active and passive grid components and systems are necessary for reliable steady state and transient analyses during normal or abnormal grid operating conditions. This paper introduces two Laplace domain-based approaches to model buck and boost DC-DC converters for electromagnetic transient studies. The first approach is an analytical one, where the converter is represented by a two-port admittance model via mo
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