With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

This study deals with the orthographic processing ability of homophones
which can account for variance in word recognition and production skills due to
phonological processing. The study aims at: A)Investigating whether the students
can recognize correct usage and spelling comprehension of different homophones
by using appropriate word that overlapped in both phonology and orthography.
B)Assessing spelling production word association to the written form of the
homophone in the sentence comprehension task. To achieve these aims, two tests
have been conducted and distributed on 50 students at first stage at the College of
Education(Ibn-Rushd) for the academic year 2010-2011. The two tests are exposed
to a jury of

Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and

In the present paper, the researcher attempts to shed some light on the objective behind inserting some Qur'anic verses by Al-Zahraa (Peace Be Upon Her) in her revered speech. Besides, it tries to investigate the hidden meaning of these verses and to study them in the light of pragmaticreferences. This task is supported by Books of Tafseer as well as the books that explained this speech to arrive at its intended meaning. It is possible say that this is astep towards studying speeches of 'Ahlul Bayt' (People of the Prophet's household) in terms of modern linguistic studies, as well as employing modern methods to explore the aesthetic values of these texts.

Language and politics go hand in hand and learning and comprehending political genre is to learn a language created for codifying, extending and transmitting political discourse in any text/talk. Drawing upon the theoretical framework of Fairclough’s CDA and Rhetoric, the current study aims at investigating Donald Trump’s First Speech, from the point of frequency and functions of some rhetorical strategies (Parallelism, Anaphora and the Power of Three, Antithesis and Expletive, etc.), Nominalization, Passivization, We-groups and Modality as well as Lexical and Textual Analysis, presented to the UN delivered on Sep. 19, 2017. Specifically, the study seeks to determine: (1) how President Trump succeeded in conveying his notions an