Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

The need for renewable energy sources is higher than ever due to rising global warming, climate change, and ozone depletion. For refrigeration and air conditioning applications, adsorption refrigeration systems are viable alternatives cooling techniques. This study is a topic and part of the M.Sc. thesis. A field solar-powered ice maker unit was created, studied, tested, and evaluated on the 13^th and 30^th of May, 2022. Activated carbon and methanol pair was used to set up a refrigeration system in Baghdad (Al Dora). Experimental tests were carried out outdoors to determine the coefficient of performance COP and specific cooling power SCP of the system. The results showed that the lowest temperature

In this research, design of advanced material for sunlight conversion requires focused research to obtain efficient photocatalytic system. Nanostructured ZnO was synthesized using spin coating technique. The structural, morphological and optical properties of annealed nanostructured ZnO thin film at 390 Co for 3 hours were characterized by x-ray diffraction, atomic force microscope AFM and UV-VIS spectrophotometer. Nanostructured ZnO was applied for removal Methylene Blue (MB) dye from water using sunlight induced photocatalytic process. Overall degradation of MB/ZnO was achieved after 120 minutes of sunlight irradiation while it needs more time for MB alone. The reaction rate constant fit pseudo first order for MB/ZnO degradation was 0.

      This work addressed the assignment problem (AP) based on fuzzy costs, where the objective, in this study, is to minimize the cost. A triangular, or trapezoidal, fuzzy numbers were assigned for each fuzzy cost. In addition, the assignment models were applied on linguistic variables which were initially converted to quantitative fuzzy data by using the Yager’sorankingi method. The paper results have showed that the quantitative date have a considerable effect when considered in fuzzy-mathematic models.

       The effect of 0.66 µeV gamma radiation on the structural and optical properties of the CdTe thin films prepared by thermal evaporation at thickness 350nm, The samples were irradiated with time (50 h and 79h) at room temperature. The absorption spectra for all the samples were recorded using UV-VIS spectrometer in order to calculate the energy gap, refractive index and others parameter . The optical energy gap was found decrease from (1.9 to 1.67) eV. 

Cryptography algorithms play a critical role in information technology against various attacks witnessed in the digital era. Many studies and algorithms are done to achieve security issues for information systems. The high complexity of computational operations characterizes the traditional cryptography algorithms. On the other hand, lightweight algorithms are the way to solve most of the security issues that encounter applying traditional cryptography in constrained devices. However, a symmetric cipher is widely applied for ensuring the security of data communication in constraint devices. In this study, we proposed a hybrid algorithm based on two cryptography algorithms PRESENT and Salsa20. Also, a 2D logistic map of a chaotic system is a

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al