Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

Objective of the study was to rate and analyze the physical fitness of female students from Iraq and Russia to find similarities, differences and regularities. Sampled for the study were 44 female non-sporting students: 20 students from Pedagogical University in Bagdad; and 24 students from Russian State University of Physical Education, Sport, Youth and Tourism in Moscow. The study was designed to obtain the joints flexibility, coordination, speed-strength and static endurance rates. The Iraqi students were tested with higher coordination abilities than their Russian peers, whilst the latter were ranked higher in the speed-strength, shoulder joints and spine flexibility tests, albeit lower than their Iraqi peers in the hip flexibility test

 The study aims to identify the relationship between Dogmatism and the behavioral problems among preparatory school students. To do this, the researcher adopted Rokeach’s scale of dogmatism, which was modified to be more appropriate of the Iraqi context. A sample of (300) students was chosen randomly to collect the needed data for the current study. To process the data, the researcher employed T-test, Pearson correlation coefficient, and Weighted Mean. The finding revealed that the study sample experience too many behavioral problems, as well as there is a positive strong relationship between Dogmatism and behavioral problems. To conclude, the researcher recommended holding counseling sessions targeting school students to mitigate

This research focuses on the difficulties that face Oud's students' in the performance of Sharif Muheyddin Haider musical works. In addition, this research suggests solutions to overcome these difficulties for make it easier to play Haider's musical works. This research also addressed important topics of great relevance the title, problem and the research's aims. Moreover, Procedures of this research adopted the descriptive approach (content analysis) to attain the research's aims. Furthermore, results and discussions where covered, and conclusions of the appropriate academic solutions were achieved to overcome the performance difficulties of Haider's musical works among Oud's students'. At the end, the research presents a set of recomme

Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s

The Mesopotamian marshlands faced a massive destruction from many years and this lead to effect to ecosystem. In this study a survey was made on the physical chemical and heavy metals characteristics and microbiological analysis of AL Chibaish marsh during the two months. Water analyses revealed unacceptable values for almost all physiochemical and biological properties, according to WHO standard limits for drinking water. Almost all major ions and heavy metal concentrations in water showed a distinct decreasing trend at the marsh outlet station compared to other stations. In general, major and minor ions, as well as heavy metals exhibit higher concentrations in location 1 than in location 3. The concentrations of heavy metals in water show