Abstract

 The current research aims to identify the analysis of the questions for the book of literary criticism for the preparatory stage according to Bloom's classification. The research community consists of (34) exercises and (45) questions. The researcher used the method of analyzing questions and prepared a preliminary list that includes criteria that are supposed to measure exercises, which were selected based on Bloom's classification and the extant literature related to the topic. The scales were exposed to a jury of experts and specialists in curricula and methods of teaching the Arabic language. The scales obtained a complete agreement. Thus, it was adapted to become a reliable instrument in this

This work aimed to produce PVA and PVA/Ag nanofibers ultra-high sensitivity photodetector by electrospinning. The electrospinning process was used to successfully prepare PVA nanofibers and a PVA-Ag nanofiber composite. FE-SEM, XRD, UV, I-V characterizations are used to study the morphological, structural, optical, and electrical properties of the material. In contrast, the PVA-Ag nanofiber composite film displayed a cubic structure with favored orientation (200) that indicated the presence of Ag NPs in the PVA-Ag nanofibers film. While the optical energy gap for PVA was 3.96 eV, it was only 2.14 eV for PVA-Ag nanofibers composite film, making this composite sensitive to visible light, particularly green light at 550 nm with a 65% photosens

A perturbed linear system with property of strong observability ensures that there is a sliding mode observer to estimate the unknown form inputs together with states estimation. In the case of the electro-hydraulic system with piston position measured output, the above property is not met. In this paper, the output and its derivatives estimation were used to build a dynamic structure that satisfy the condition of strongly observable. A high order sliding mode observer (HOSMO) was used to estimate both the resulting unknown perturbation term and the output derivatives. Thereafter with one signal from the whole system (piton position), the piston position make tracking to desire one with a simple linear output feedback controller after ca

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f

Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T

Experiment was conducted in Baghdad, three factor were used in this research included Two types of Plows included moldboard and disk plows which represented the main plot, Three forward speeds of the tillage was the second factor included 1.85, 3.75 and 5.62 km / h which represented sup plot , and Three levels of Soil Moisture was third factor included 21, 18 and 14 % in all of Vertical and Lateral Plowing Deviation, Practical and specific productivity, actual time for plowing one donam and appearance (goodness) of Tillage represented by the number of clods > 10 cm in silt clay loam soil with depth 22 cm were studied. the experiment was used Split – split plot design under randomized complete block design with three replications and Le

Background: Breast cancer is the first one among Iraqi females. Most of them present later for diagnosis. Early detection center in tertiary hospital practice uses FNAB for early diagnosis. Publications on accuracy of this detection are scarce.

Objective:  To test the accuracy of FNAB in breast lump diagnosis.

Methods: Diagnostic test accuracy study, on 204 women with breast lump, attending the oncology department in 2017.

Results: Fine-needle aspiration biopsy diagnosis of histologically malignant cases were, malignant in 89 (87.3%), suspicious of malignancy in 5 (4.9%), and benign in 4 (3.9%). Complete sensitivity was 87.3%, and specificity