Preferred Language
Articles
/
cxhX55QBVTCNdQwCICJy
Posters in Vocabulary Learning
...Show More Authors

An essential element in English as a foreign language (EFL) learning is vocabulary. There is a big emphasis on learning the new words' meaning from the books or inside classrooms. Also, it is a major part of language teaching as well as being fundamental to the learner but there is a big challenge in vocabulary instruction due to the weak confidence by teachers in selecting the suitable practice in teaching vocabulary or they sometimes unable to specify a suitable time for it during the teaching process. The major aim of this study is to investigate the value of posters in vocabulary learning on the 2nd grade students at Halemat Alsaadia High School in Baghdad – Iraq. It hypothesized that there are no statistically significant differences between the experimental and control groups' scores in the post-test. Participants were randomly assigned to two groups out of four groups. Group A which represents the control group are taught without using posters, and group B which represents the experimental group is taught by using posters. The whole number of participated students is 62 students. The control group is (32) , and the experimental group is (30) students. Students were subjected to pre and posttests. The researcher used the T-test for two independent samples to know the equivalent between the experimental and control groups in the pretest. The researcher used chi-square to find out statistically significant differences between the experimental and control groups' variables of mothers and fathers' academic achievement. The results of the post-test shown that there are differences between the experimental and control groups for the favor of the experimental group. It is concluded that teaching vocabulary by using posters proved to be more useful for the students of Intermediate school than through taught without using posters. This adequacy of using posters is clear on developing both memorizing and written achievement. The present study suggests that English teachers in Iraq need to activate their students' minds and memorization through using posters and recommends that other researchers to research the effectiveness of Facebook and social media in increasing English language vocabulary learning.

Clarivate Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Using VGG Models with Intermediate Layer Feature Maps for Static Hand Gesture Recognition
...Show More Authors

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

... Show More
View Publication Preview PDF
Scopus (9)
Crossref (3)
Scopus Crossref
Publication Date
Fri Aug 16 2024
Journal Name
International Journal Of Mathematics And Computer Science
Artificial Intelligence Techniques to Identify Individuals through Palm Image Recognition
...Show More Authors

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

... Show More
View Publication Preview PDF
Scopus (6)
Crossref (3)
Scopus Clarivate Crossref
Publication Date
Sun Apr 28 2024
Journal Name
Journal Of Advances In Information Technology
Enhancement of Recommendation Engine Technique for Bug System Fixes
...Show More Authors

This study aims to develop a recommendation engine methodology to enhance the model’s effectiveness and efficiency. The proposed model is commonly used to assign or propose a limited number of developers with the required skills and expertise to address and resolve a bug report. Managing collections within bug repositories is the responsibility of software engineers in addressing specific defects. Identifying the optimal allocation of personnel to activities is challenging when dealing with software defects, which necessitates a substantial workforce of developers. Analyzing new scientific methodologies to enhance comprehension of the results is the purpose of this analysis. Additionally, developer priorities were discussed, especially th

... Show More
View Publication Preview PDF
Scopus Clarivate Crossref
Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
SBOA: A Novel Heuristic Optimization Algorithm
...Show More Authors

A new human-based heuristic optimization method, named the Snooker-Based Optimization Algorithm (SBOA), is introduced in this study. The inspiration for this method is drawn from the traits of sales elites—those qualities every salesperson aspires to possess. Typically, salespersons strive to enhance their skills through autonomous learning or by seeking guidance from others. Furthermore, they engage in regular communication with customers to gain approval for their products or services. Building upon this concept, SBOA aims to find the optimal solution within a given search space, traversing all positions to obtain all possible values. To assesses the feasibility and effectiveness of SBOA in comparison to other algorithms, we conducte

... Show More
View Publication Preview PDF
Scopus (8)
Crossref (6)
Scopus Crossref
Publication Date
Fri Mar 24 2023
Journal Name
Arab World English Journal
PRAGMATIC AWARENESS OF SPEECH ACTS, POLITENESS, AND GRICE MAXIMS OF IRAQI EFL POSTGRADUATE STUDENTS الوعي التداولي لافعال الكلام والتأدب والاقوال المأثورة لطلبة الدراسة العليا في اللغة الانجليزية كلغة اجنبية
...Show More Authors

This study examines postgraduate students’ awareness of pragmatic aspects, including Grice Maxims, Politeness, and Direct and Indirect forms of speech. According to Paul Grice’s theory of implicature, which is considered one of the most important contributions to pragmatics, this paper discusses how postgraduate students can meet the cooperative principle when communicating effectively. It also outlines how does politeness principles influence obeying or violating the maxims and how is the use of direct or indirect forms of utterances prompted by politeness. Sixteen master’s students of Linguistics and Literature were asked to take a multiple-choice test. The test will be represented along with the interpretation of each optio

... Show More
Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
...Show More Authors

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

... Show More
View Publication Preview PDF
Scopus (5)
Crossref (3)
Scopus Crossref
Publication Date
Fri May 01 2020
Journal Name
International Journal Of Advanced Science And Technology
Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval
...Show More Authors

Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN

... Show More
Publication Date
Sat Jul 06 2024
Journal Name
Multimedia Tools And Applications
Text classification based on optimization feature selection methods: a review and future directions
...Show More Authors

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.

... Show More
View Publication Preview PDF
Scopus (2)
Crossref (4)
Scopus Crossref
Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Human Pose Estimation Algorithm Using Optimized Symmetric Spatial Transformation Network
...Show More Authors

Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

... Show More
View Publication Preview PDF
Scopus (2)
Scopus Crossref
Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
...Show More Authors

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

... Show More
View Publication Preview PDF