This study aimed to statement jet stream and its impact in the anti-cyclone affecting the climate of Iraq. Through the use of simple correlation coefficient ( Pearson ) that there is a very strong relationship between high- Siberian and both of the jet stream especially during the winter or over the stations of North . Therefore we, observe the relationship be significant in most of the winter months , spring and autumn . Statistically significant , but are different between station and another station , while the study come to another Anti-ciyclon have a real ,significant and statistically relationship corrclation . But this relationship is less than which found in are much less it with the Siberian high , it depends on the type of stat

Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat

            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

Since its invention by the Ancient Romans and later developed during the mid-18th century, the concrete structure and finish, has been considered as the most powerful, practical, economic and constructional material that meets the building’s architectural and aesthetical requirements. By creating unique architectural forms, the pioneer architects used concrete widely to shape up their innovative designs and buildings.

The pre-mixed ultra-high performance concrete which manufactured by Lafarge.

The transparent concrete and cement that allow the light beams to pass through them, introduces remarkable well-lit architectural spaces within the same structural criteria. This product is a recyclable, sustainab

The follower to study the markets in the Islamic Mashreq (Iraq, Persia and the country of Ma
Behind the river for the period from the reign of the Prophet Muhammad until the end of the Islamic era) to find that there
A remarkable development in the pattern, shape, planning and privatization of markets
Islamic cities and places are the main conditions for their existence, which is the mosque of the mosque
And markets, and these markets have evolved from being a space in which there are no building and no ceilings to shade them in
The places of sale and purchase to specialized markets classified according to the materials and goods produced in them
This would facilitate the task of supervising it by the market factor and

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne