This study was planned to evaluate the renal function tests and liver function tests and it carried out in Al-Yarmouk hospital,Baghdad –Iraqin patients withtype 1 and type 2 diabetes mellitus by measuring(uric acid,urea and creatinine) ,Aspartate aminotransferase (AST) and Alanine aminotransferase (ALT). Seventy five individuals of Iraqi adults (male) were divided into three groups, 25 patients with type1 diabetes mellitus ,25 patients with type 2 diabetes mellitus and 25 normal individuals were taken as control group. The mean value of uric acid, urea and creatinine was higher significantly in patients thanin control group (P< 0.05),while the correlation(p< 0.01) between age ,creatinine in type 1 and between age and (Urea, Uric acid ,cr

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

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 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

Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform wit

            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

One of the most important intellectual issues, which receive attention is the issue of modernity, it has occupied the scholars of all time. However, modern poetry used to have special care in Iraq and in the Arab countries .. it is not strange that the concept of modernity is linked to history .. or having history as the most important dimension of its dimensions .. because Arab poetry is historical and it is moving into an area of ​​the past that is still active in terms of language and literary image .. When some poets found that changing and modernizing poetry became a necessity of evolution, and one of the fundamentals of modernization, the cultural impact did not respond to the desire of poets, and their impulse in modern poetry

The genus Ziziphus is one of the Family Rhamnaceae and consists of more than 170 species distributed in tropical and subtropical regions. All the species in the genus are of economical and medical importance. This study was conducted to identify the morphologically and anatomically features of the genus in Iraq.  The field survey was conducted across the study area where 4 species (Ziziphus jujube, Z. mauritiana, Z. nummularia and Z. spina-christi) were collected and used in the study.  The result showed that there is variation in morphological and anatomical features among the species in the stem cross-section and longitudinal section of leaves also the differences appeared in the epidermis of leaves.