Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an SVM-based DDoS detection model shows superior performance. This comparative analysis offers a valuable insight into the development of efficient and accurate techniques for detecting DDoS attacks in SDN environments with less complexity and time.
Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area. The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and
... Show MoreIn this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes
This study focuses on evaluating the suitability of three interpolation methods in terms of their accuracy at climate data for some provinces of south of Iraq. Two data sets of maximum and minimum temperature in February 2008 from nine meteorological stations located in the south of Iraq using three interpolation methods. ArcGIS is used to produce the spatially distributed temperature data by using IDW, ordinary kriging, and spline. Four statistical methods are applied to analyze the results obtained from three interpolation methods. These methods are RMSE, RMSE as a percentage of the mean, Model efficiency (E) and Bias, which showed that the ordinary krigingis the best for this data from other methods by the results that have b
... Show MoreMany Iraqi provinces had collective cemeteries, especially in the middle and southern regions of Iraq, but many of those cemetery locations are undefined yet. Ground penetration radar has two features that make it optimal from a geophysical perspective for shallowly detecting sensitive materials near the surface. First, the instantaneous image is formed upon scanning, called a radargram. Second, the non-destructive inference of the scanned materials. For these two reasons, this technique was chosen to conduct a simulation process to reveal the old human remains in Iraq's central and southern areas using another model with the same physical feature (old burial) at the AL-Khamisiya site, Thi-Qar province.
The demanded stage
... Show MoreBackground: lip lengthening procedure is one of the surgical options for the correction of gummy smile in patients with short upper lip. Methods: A comparative clinical study was conducted on 15 patients requiring lip lengthening procedure for the esthetic correction of excessive gingival exposure with gummy smile. Scalpel was used in seven patients and diode laser in the remaining eight patients. Under infiltration anesthesia, about one cm strip of mucosa was excised at the vestibular depth and the mucosa of the lip was sutured to the alveolar mucosa. Results: The diode laser group demonstrated less postoperative pain and swelling. Regarding postoperative ecchymosis, three patients in the scalpel group developed ecchymosis and no cases
... Show MoreBecause of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.
To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a
... Show MoreLand Use / Land Cover (LULC) classification is considered one of the basic tasks that decision makers and map makers rely on to evaluate the infrastructure, using different types of satellite data, despite the large spectral difference or overlap in the spectra in the same land cover in addition to the problem of aberration and the degree of inclination of the images that may be negatively affect rating performance. The main objective of this study is to develop a working method for classifying the land cover using high-resolution satellite images using object based method. Maximum likelihood pixel based supervised as well as object approaches were examined on QuickBird satellite image in Karbala, Iraq. This study illustrated that
... Show MoreSince the inflammatory factor IL-6 known by its critical role in different metabolic reactions in the
body, therefore, this study was designed to detect it is effect in the thyroid gland function by
injecting three groups of rats, the first with IL-6 , the second with carbimazole (antithyroid drug) and
the third with normal saline (Control).The experiment included three groups of rat; each was injected
with recombinant human interleukin-6 (rhIL-6), Carbimazole, or normal saline (Control). The results
of experiments showed that both IL-6 and carbimazole caused a decrease in the levels of thyroid
hormones (T3 and T4) in animal sera, and a significant decrease in animal body weight, but had no
effect on the liver weight