Ultimate oil recovery and displacement efficiency at the pore-scale are controlled by the rock wettability thus there is a growing interest in the wetting behaviour of reservoir rocks as production from fractured oil-wet or mixed-wet limestone formations have remained a key challenge. Conventional waterflooding methods are inefficient in such formation due to poor spontaneous imbibition of water into the oil-wet rock capillaries. However, altering the wettability to water-wet could yield recovery of significant amounts of additional oil thus this study investigates the influence of nanoparticles on wettability alteration. The efficiency of various formulated zirconium-oxide (ZrO2) based nanofluids at different nanoparticle concentrations (0

Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

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

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

Microalgae have been increasingly used for wastewater treatment due to their capacity to assimilate nutrients. Samples of wastewater were taken from the Erbil wastewater channel near Dhahibha village in northern Iraq. The microalga Coelastrella sp. was used in three doses (0.2, 1, and 2g. l^-1) in this experiment for 21 days, samples were periodically (every 3 days) analyzed for physicochemical parameters such as pH, EC, Phosphate, Nitrate, and BOD₅, in addition to, Chlorophyll a concentration. Results showed that the highest dose 2g.l^-1 was the most effective dose for removing nutrients, confirmed by significant differences (p≤0.05) between all doses. The highest removal percentage was

This study aimed to assess the efficiency of Nerium oleander in removing three different metals (Cd, Cu, and Ni) from simulated wastewater using horizontal subsurface flow constructed wetland (HSSF-CW) system. The HSSF-CW pilot scale was operated at two hydraulic retention times (HRTs) of 4 and 7 days, filled with a substrate layer of sand and gravel. The results indicated that the HSSF-CW had high removal efficiency of Cd and Cu. A higher HRT (7 days) resulted in greater removal efficiency reaching up to (99.3% Cd, 99.5% Cu, 86.3% Ni) compared to 4 days. The substrate played a significant role in removal of metals due to adsorption and precipitation. The N. oleander plant also showed a good tolerance to the uptake of Cd, Cu, and Ni ions fr