This paper studies the demonstratives as deictic expressions in Standard Arabic and English by outlining their phonological, syntactic and semantic properties in the two languages. On the basis of the outcome of this outline, a contrastive study of the linguistic properties of this group of deictic expressions in the two languages is conducted next. The aim is to find out what generalizations could be made from the results of this contrastive study.

The seizure epilepsy is risky because it happens randomly and leads to death in some cases. The standard epileptic seizures monitoring system involves video/EEG (electro-encephalography), which bothers the patient, as EEG electrodes are attached to the patient’s head.

Seriously, helping or alerting the patient before the seizure is one of the issue that attracts the researchers and designers attention. So that there are spectrums of portable seizure detection systems available in markets which are based on non-EEG signal.

The aim of this article is to provide a literature survey for the latest articles that cover many issues in the field of designing portable real-time seizure detection that includes the use of multiple

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

Between the 1980s and 1990s, the HURIER model was developed by Brownell and consist of six interrelated components, which are represented in these acronyms (Hearing, Understanding, Remembering, Interpreting, Evaluating, and Responding). This model can be considered as a framework of the behavioral approach which can be used to improve students’ listening performance and to foster a positive attitude toward listening. Many learners find it challenging to improve their listening skills when learning a second or foreign language because it requires the integration of both listening and speaking. Consequently, enhancing this skill will help students improve other language skills, including reading, speaking, and writing. The HURI

One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first