The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr

Al-Rustamiyah plant is the oldest and biggest sewage treatment plant in Iraq; it locates in the south of Baghdad city. The plant suffers from serious problems associated with overflow and low capacity. The present work aims to upgrade the heart of biological treatment process through suggesting the use of membrane bioreactor; (MBR). In this work, fouling of membrane during sewage treatment has been analyzed experimentally and theoretically by fouling mechanisms. Aeration has been applied in order to control fouling through producing effective diameters of air bubbles close to the membrane walls. Effect of air flow rate on flux decline was investigated. Hermia's models were used to investigate the fouling mechanisms. The results showed th

   Today, dimethyl ether (DME) is changing to ordinarily worn as a superb aerosol propellant and refrigerant for its eco-friendly characteristics. Lately, with the development of novel chemical energy in the coal industries, it has become a fascinating field of research as an alternative green fuel for diesel machines due to the high cetane number. The DME synthesis processes include catalytic dehydrating methanol in an adiabatic fixed-bed reactor. In this study, to investigate the chemical conditions of the methanol dehydration reaction, CFD simulations of the adiabatic reactor have been assessed. The advantage of the work is a sensitivity analysis was run to find the effect of pressure, kinetics, and velocity on the reactor performan

An experimental study was conducted on pressure drop of water flow through vertical cylindrical packed beds in turbulent region and the influence of the operating parameters on its behavior. The bed packing was made of spherical and non-spherical particles (spheres, Rasching rings and intalox saddle) with aspect ratio range 3.46  D/dp  8.486 obtaining bed porosities 0.396 0.84 and Reynolds number 1217  21758. The system is consisted of 5 cm inside diameter Perspex column, 50 cm long; distilled water was pumped through the bed with flow rate 875, 1000, 1125, 1250,1375 and 1500 l/h and inlet water temperature 20, 30, 40 and 50 ˚C. The packed bed system was monitored by using LabVIEW program, were the result

يسعى المجتمع من خلال الوحدات الإقتصادية إلى الوصول إلى تحقيق أفضل الإنجازات التي لا تتمثل بالسلع والخدمات حسب وإنما بما يتحقق من مردود لكافة الاطراف المعنية بالوحدات الإقتصادية على ان لايتم ذلك على حساب قيم المجتمع وأخلاقياته وآدابه العامة. وعليه تصبح الوحدات الإقتصادية مسرحاً لصراعات قوى متعددة كل منها له قيمه الأخلاقية سواء كان فرداً أومجموعة افراد أو وحدة إقتصادية أو أي جهة أُخرى، وبحكم مسؤولياته

Presupposition is the background belief that is known by both the speaker and the addressee, it is tied to particular words and aspects of the surface structure that act as linguistic triggers. The present study aims at investigating whether Iraqi fourth -year university students are able to recognize the English presuppositions through the meaning of these linguistic triggers .To fulfil the basic requirements of the study, the researcher has conducted a test . The results of the study have validated the hypothesis of the work and it is found that the linguistic triggers are important tools in recognizing presuppositions.    

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 dete

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative