The survey and checklist of invasive species of the insects in some different localities of Iraq are revised; 24 invasive species were documented until December 2018 during the current investigations. The species distributions, common names and synonyms are given.

The current investigation included all of exotic species in Iraq, which are not collected during this study.

    A total of 533 specimens were collected in survey of Brachyceran species from different regions of Iraq during February to November 2014 .This study was reported 16 species belonging to 13 genera and 7 families, the results showed that Dicranosepsis Duda, 1926 (Family; Sepsidae) is  recorded the genus  for the first time in Iraq.

This research proposes the application of the dragonfly and fruit fly algorithms to enhance estimates generated by the Fama-MacBeth model and compares their performance in this context for the first time. To specifically improve the dragonfly algorithm's effectiveness, three parameter tuning approaches are investigated: manual parameter tuning (MPT), adaptive tuning by methodology (ATY), and a novel technique called adaptive tuning by performance (APT). Additionally, the study evaluates the estimation performance using kernel weighted regression (KWR) and explores how the dragonfly and fruit fly algorithms can be employed to enhance KWR. All methods are tested using data from the Iraq Stock Exchange, based on the Fama-French three-f

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

Fresh vegetables are an important part of a healthy diet. The consumption of raw vegetables without cooking or good washing can be a major rout of transmission to the parasitic infection. The goal of this study was to determine the intestinal parasitic contamination of fresh vegetables from vegetables sales markets in Baghdad province during the different above months of the year. A total of 303 samples of different vegetables were randomly selected from three wholesale markets distributed through different regions in Baghdad (East, West and South) and then were examined by a floatation method. The present study showed that the collected vegetables were contaminated with 12 species of intestinal parasites, and the total percentage of contam

The background subtraction is a leading technique adopted for detecting the moving objects in video surveillance systems. Various background subtraction models have been applied to tackle different challenges in many surveillance environments. In this paper, we propose a model of pixel-based color-histogram and Fuzzy C-means (FCM) to obtain the background model using cosine similarity (CS) to measure the closeness between the current pixel and the background model and eventually determine the background and foreground pixel according to a tuned threshold. The performance of this model is benchmarked on CDnet2014 dynamic scenes dataset using statistical metrics. The results show a better performance against the state-of the art