The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices’ power usage. Also, a rand order code (ROC) technique is used with SNN to detect cyber-attacks. The proposed method is evaluated by comparing its performance with two other methods: IDS-DNN and IDS-SNNTLF by using three performance metrics: detection accuracy, latency, and energy usage. The simulation results have shown that IDS-SNNDT attained low power usage and less latency in comparison with IDS-DNN and IDS-SNNTLF methods. Also, IDS-SNNDT has achieved high detection accuracy for cyber-attacks in contrast with IDS-SNNTLF.
The article aims to consider the concept of language metaphor in Russian and Arabic languages and the problem of metaphor functioning in language, since it is one of the most important figurative components of the structural organization of the text and an important means of reflecting the national culture of each people. and often in revealing the image of a metaphor one can feel the full flexibility of the language and its beauty.
The degree of the woman’s satisfaction on clothing depends, to a large extent, on the body measurements. If clothing is very wide, it shows her enormous and if it is too tight it may draw attention to the defects of the body. It may also lead to the compatibility or incompatibility of clothing with fashion. Whatever the quality of the garment in terms of sewing and design, the costume which is not suitable for body size may affect the physical style negatively and may give the wearer an improper look. Clothing was carried out without measurements and did not use models (templates). The method of preparation affected the overall appearance because it often did not fit the shape of the body completely. Therefore, people thought in many w
... Show MoreThe remediation oil production by matrix acidizing method on the well named "X" (for confidential reasons) is scrutinized in this paper. Initial production of 1150 bpd, production index of 2.8 STB/Psi/d and permeability of 150md, in 2018 two years down the lane this dropped to 450 bpd, production index 0.7 STB/Psi/d. The declined observed on the production index is trouble shouted and after elimination of (no completion damage/perforation damage), the skin is calculated by carrying out a well test (build-up test) whose extrapolation in excel over times gave us a skin of 40.The reservoir heterogeneity, containing >20% of feldspar, carbonates and paraffin’s guided thematrix acidizing design and treatment proposition to remedy thi
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The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.
The study aims to explore the effect of cognitive behavioral therapy on internet addiction among university students. The experimental method was used. The study population consisted of (100) university students (50 males, 50 females). The Research sample included (13) University students at Baghdad University addicted to the Internet (9 males, 4 females), divided into two groups: a control group consisting of (6) individuals (4 males, 2 females) and an experimental sample consisting of (6) individuals (4 males, 2 females). The Scale of Internet Addiction by Young (1996), which was translated and modified into the Arabic language by (Moegel and Prism, 2016), was administered to the study sample. The sample was subjected to two sess
... Show MoreUsing the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result
... Show MoreIn this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.
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Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu
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Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result
... Show More