Abstract

The traffic jams taking place in the cities of the Republic of Iraq in general and the province of Diwaniyah especially, causes return to the large numbers of the modern vehicles that have been imported in the last ten years and the lack of omission for old vehicles in the province, resulting in the accumulation of a large number of vehicles that exceed the capacity of the city's streets, all these reasons combined led to traffic congestion clear at the time of the beginning of work in the morning, So researchers chose local area network of the main roads of the province of Diwaniyah, which is considered the most important in terms of traffic congestion, it was identified  fuzzy numbers for

In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

The technological developments in the field of communication have witnessed considerable impact in the variables which exist in following up and conveying the events which link it’s meaning to political implications. This makes a number of satellite channels depend on the techniques of propaganda and use them in the news bulletins to achieve political aims and ends related to its formational directives where those channels allotted a considerable time in its programming transmission map to concentrate on the security and political status to complete the image of the informational scene according to the logic of its propaganda and styles in processing news for daily events.The technological developments in the field of communication hav

     The sunrise, sunset, and day length times for Baghdad (Latitude =33.34º N, Longitude =44.43º E) were calculated with high accuracy on a daily basis during 2019. The results showed that the earliest time of sunrise in Baghdad was at 4h: 53m from 5 Jun. to 20 Jun while the latest was at 7h: 07m from 5 Jan. to 11 Jan. The earliest time of sunset in Baghdad was at16 h: 55m from 30 Nov. to 10 Dec. whereas the latest was at 19h: 16m from 25 Jun. to 5 Jul. The minimum period of day length in Baghdad was 9h: 57m) in 17 Dec. whereas the maximum period was 14h: 22m) in 20 Jun. Day length was calculated and compared among regions of different latitudes(0, 15, 30, 45 and 60 north).

Storage of rainwater within the root depth zone is one of the modern ways to increase plant production. Subsurface water retention technology was applied to assess improving values of crop yield and crop water use efficiency, applying a membrane made of low-density polyethylene trough installed below the crop root zone. The goal of this paper is to assess that the retention of rainwater above the membrane can improve the crop yield and crop water use efficiency values for winter wheat. The experiment was conducted in open field, within Joeybeh Township, located in east of the Ramadi City, in Anbar Province, in winter growing season 2018-2019. Two plots T1 (with membrane trough) and T2 (without membrane) were used for the

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

      Field trial was conducted with the aim of utilizing extract of allelopathic crop to reduce the use of synthetic herbicides in wheat fields. Sorghum extract at 12 L /ha, sunflower extract at 12 L /ha, combination of sorghum and sunflower extracts at 12 L /ha and chevalier at 25, 50 and 100% of recommended dose were applied alone or in combination with each other. Weed free and weedy check treatments were included for comparison. The experiment was conducted in a randomized complete block design with three replications. The results showed that the recommended  dose of chevalier  treatment recorded lowest means of weed density 15.7, 23.7, 25.3 and 27.9 weeds m-2and weeds dry weight 13.4, 16.4, 23.3 and 29.2 g m-2 and gave