The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficient between the actual and predicted values for fluoride concentration at the six locations, Al-Karakh, East Tigris, Al-Wathbah, AL-Karamah, Al-Rashid and Al-Wahda WTP intakes, was 0.93, 0.82, 0.86, 0.90, 0.83 and 0.89, respectively. Model verification results indicated that the model forecasting outputs rationally estimated the actual monthly fluoride content in the selected locations.
In this research velocity of moving airplane from its recorded digital sound is introduced. The data of sound file is sliced into several frames using overlapping partitions. Then the array of each frame is transformed from time domain to frequency domain using Fourier Transform (FT). To determine the characteristic frequency of the sound, a moving window mechanics is used, the size of that window is made linearly proportional with the value of the tracked frequency. This proportionality is due to the existing linear relationship between the frequency and its Doppler shift. An algorithm was introduced to select the characteristic frequencies, this algorithm allocates the frequencies which satisfy the Doppler relation, beside that the tra
... Show MoreIn the current research, an eco-biosynthesis method for synthesizing silver nanoparticles (AgNPs) is reported using thymus vulgaris leaves (T. vulgaris) extracts. The optical and structural properties of the nanoparticles is determined using UV-visible, x-ray diffraction (XRD) and field emission scanning electron microscope (FESEM). In addition, the synthesis factors such as the temperature, the molar ratio of silver nitride and thymus vulgaris leaves extract have been investigated. The XRD pattern presented higher intensity for the five characteristic peaks of silver. FESEM images for same samples indicated that the particle size was distributed between 24-56 nm. In addition, it’s observed the formation of some aggregated Ag particles
... Show MoreDistributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks
... Show MoreThe hydroconversion of Iraqi light straight run naphtha was studied on zeolite catalyst. 0.3wt.%Pt/HMOR catalyst was prepared locally and used in the present work. The hydroconversion performed on a continuous fixed-bed laboratory reaction unit. Experiments were performed in the temperature range of 200 to 350°C, pressure range of 3 to 15 bars, LHSV range of 0.5-2.5h-1, and the hydrogen to naphtha ratio of 300.
The results show that the hydroconversion of Iraqi light straight naphtha increases with increase in reaction temperature and decreases with increase in LHSV.
High octane number isomers were formed at low temperature of 240°C. The selectivity of hydroisomerization improved by increasing reaction pressu
... Show MoreIn this work, the study of
The term "tight reservoir" is commonly used to refer to reservoirs with low permeability. Tight oil reservoirs have caused worry owing to its considerable influence upon oil output throughout the petroleum sector. As a result of its low permeability, producing from tight reservoirs presents numerous challenges. Because of their low permeability, producing from tight reservoirs is faced with a variety of difficulties. The research aim is to performing hydraulic fracturing treatment in single vertical well in order to study the possibility of fracking in the Saady reservoir. Iraq's Halfaya oil field's Saady B reservoir is the most important tight reservoir. The diagnostic fracture injection test is determined for HF55using GOHFER soft
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Abstract
The aim of the present work is to control of metal buried corrosion by alteration the media method. This method depended on the characteristics of each media. The corrosion rates in different media (soil, sand, porcelanite stone and gravel) for specimens of low carbon steel were measured by two methods weight loss method and polarization method, weight loss measured by buried specimens in these medias separately for 90 days. The polarization method includes preparing of specimen and salt solutions have electrical resistivity equivalent electrical resistivity of these media. The corrosion rate of two method results in (soil > sand> porcelainte stone> gravel). The lower corrosion rate happene
... Show More<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
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