Background: Sprite coding is a very effective technique for clarifying the background video object. The sprite generation is an open issue because of the foreground objects which prevent the precision of camera motion estimation and blurs the created sprite. Objective: In this paper, a quick and basic static method for sprite area detection in video data is presented. Two statistical methods are applied; the mean and standard deviation of every pixel (over all group of video frame) to determine whether the pixel is a piece of the selected static sprite range or not. A binary map array is built for demonstrating the allocated sprite (as 1) while the non-sprite (as 0) pixels valued. Likewise, holes and gaps filling strategy was utilized to re

      Cyberbullying is one of the biggest electronic problems that takes multiple forms of harassment using various social media. Currently, this phenomenon has become very common and is increasing, especially for young people and adolescents. Negative comments have a significant and dangerous impact on society in general and on adolescents in particular. Therefore, one of the most successful prevention methods is to detect and block harmful messages and comments. In this research, negative Arabic comments that refer to cyberbullying will be detected using a support vector machine algorithm. The term frequency-inverse document frequency vectorizer and the count vectorizer methods were used for feature extraction, and the results wer

Malaria is a curative disease, with therapeutics available for patients, such as drugs that can prevent future malaria infections in countries vulnerable to malaria. Though, there is no effective malaria vaccine until now, although it is an interesting research area in medicine. Local descriptors of blood smear image are exploited in this paper to solve parasitized malaria infection detection problem. Swarm intelligence is used to separate the red blood cells from the background of the blood slide image in adaptive manner. After that, the effective corner points are detected and localized using Harris corner detection method. Two types of local descriptors are generated from the local regions of the effective corners which are Gabor based f

Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

Heart disease identification is one of the most challenging task that requires highly experienced cardiologists. However, in developing nations such as Ethiopia, there are a few cardiologists and heart disease detection is more challenging. As an alternative solution to cardiologist, this study proposed a more effective model for heart disease detection by employing random forest and sequential feature selection (SFS). SFS is an effective approach to improve the performance of random forest model on heart disease detection. SFS removes unrelated features in heart disease dataset that tends to mislead random forest model on heart disease detection. Thus, removing inappropriate and duplicate features from the training set with sequential f

Fifty of urine samples were collected from patients with urinary tract infection
(UTI). The samples were collected from AL- Yarmuk hospital in Baghdad. All of
the isolates were diagnosed using biochemical test and vitek. The result showed that
30 (60%) isolates identified as E.coli from 50 urine samples. The colicinogenic
isolates were determined using cup assay methods. The results showed that 10 out of
30 isolates (33.3%) were detect as colicin producers from 30 isolate identified as
E.coli depending on the clear zone that observed against the sensitive isolate.
Colicin was extracted from the efficient isolate. Colicin activity (320 U/ml) was
determined by well assay method. The protein concentration (520 μg /m

     The present study was undertaken to determine and compare the antibacterial and biochemical characteristics of honey samples from Kurdistan region in Iraq and Arabian Gulf region. Sixteen honey samples of mixed floral origins from both regions were analysed and compared. Antibacterial activity of the honey samples was investigated against five clinical pathogenic bacteria: Acinetobacter baumannii, Escherichia coli, Pseudomonas aeruginosa, Salmonella typhi and Staphylococcus aureus by agar dilution method. Both sample sets showed differential biochemical characteristics and potential functional properties such as antioxidant and antimicrobial properties. All measured parameters were within accepted ranges. Howev