One of the prominent goals of Metrical Phonology Theory is providing stress of poetry on the syllable-, the foot-, and the phonological word- levels. Analysing poetry is one of the most prominent and controversial issues for the involved number and types of syllables, feet, and meters are stable in poetry compared to other literary texts. The prosodic seeds of the theory have been planted by Firth (1948) in English, while in Arabic يديهارفلا in the second half of the eighth century (A.D.) has done so. Investigating the metrical structure of poetry has been conducted in various languages, whereas scrutinising the metrical structure of English and Arabic poetry has received little attention. This study aims at capturing the

Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

planning is among the most significant in the field of robotics research.  As it is linked to finding a safe and efficient route in a cluttered environment for wheeled mobile robots and is considered a significant prerequisite for any such mobile robot project to be a success. This paper proposes the optimal path planning of the wheeled mobile robot with collision avoidance by using an algorithm called grey wolf optimization (GWO) as a method for finding the shortest and safe. The research goals in this study for identify the best path while taking into account the effect of the number of obstacles and design parameters on performance for the algorithm to find the best path. The simulations are run in the MATLAB environment to test the

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

Acromegaly is ametabolic disorder characterized by an acquired progressive somatic disfigurement, mainly involving the face, extremities and many other organs, that are associated with systemic manifestations, caused by excessive secretion of growth hormone and a resultant persistent elevation of insulin-like growth factor-I concentrations. In more than 90% of cases originates from a monoclonal benign pituitary adenoma. Aim of this study to assess the level of insulin-like growth factor-I (IGF-I) in saliva of acromegalic patients, and to compare it with the basal levels of serum IGF-I. Sixty specimens of serum and saliva collected from two groups of subjects (forty acromegalic patients and twenty healthy persons). The specimens were