Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

Zernike Moments has been popularly used in many shape-based image retrieval studies due to its powerful shape representation. However its strength and weaknesses have not been clearly highlighted in the previous studies. Thus, its powerful shape representation could not be fully utilized. In this paper, a method to fully capture the shape representation properties of Zernike Moments is implemented and tested on a single object for binary and grey level images. The proposed method works by determining the boundary of the shape object and then resizing the object shape to the boundary of the image. Three case studies were made. Case 1 is the Zernike Moments implementation on the original shape object image. In Case 2, the centroid of the s

Based on collections made during March to September 2012. A totals of 58 species belong to 33 genera were identified from extra north to extra south of Erbil governorate, among them 30 species are registered as a new record to flora of Iraq. Most attention was paid to the most common and abundant lichens that present almost in most locations, which were Collema cristatum, Diploschistes scruposus, Lecanora dispersa, Lecanora murales, Pertusaria flavicunda, Placidium lacinulatum, Thelomma californicum and Verrucaria Maura.

Studies in Iraq that concerned identification of free-living Protozoa (sarcodina) are scarce; so the current study deals with these protozoan communities inhabiting the Tigris River in Baghdad City. Sampling collection stations have been selected at each of AL-Gheraiˈat and AL-Adhamiyah area adjacent to the river. Monthly intervals sampling with three samples were collected from each station from June to September 2020. Total of 23 sarcodina taxa were listed, out of them 5 taxa were new record to the Tigris River in Baghdad: Difflugia urceolata Carter, 1864 (Arcellinida, Difflugiidae), Heleopera perapetricola Leidy, 1879 (Arcellinida, Heleoperidae), Rhaphidiophrys pallida F.E. Schulze, 1874 (Centrohelida, Raphidiophridae), Saccamoeba sp