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An automatic lip reading for short sentences using deep learning nets
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One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jones to detect the face area. Then 68 landmarks of the facial area are determined, and the landmarks from 48 to 68 represent the lip area extracted based on building a binary mask. Then, the contrast is enhanced to improve the quality of the lip image by applying contrast adjustment. Finally, sentences are classified using two deep learning models, the first is AlexNet, and the second is VGG-16 Net. The database consists of 39 participants (32 males and 7 females). Each participant repeats the short sentences five times. The outcomes demonstrate the accuracy rate of AlexNet is 90.00%, whereas the accuracy rate for VGG-16 Net is 82.34%. We concluded that AlexNet performs better for classifying short sentences than VGG-16 Net.

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Publication Date
Wed Aug 05 2020
Journal Name
Advances In Civil Engineering
Strength compensation of deep beams with large web openings using carbon fiber–reinforced polymer sheets
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This article presents the results of an experimental investigation of using carbon fiber–reinforced polymer sheets to enhance the behavior of reinforced concrete deep beams with large web openings in shear spans. A set of 18 specimens were fabricated and tested up to a failure to evaluate the structural performance in terms of cracking, deformation, and load-carrying capacity. All tested specimens were with 1500-mm length, 500-mm cross-sectional deep, and 150-mm wide. Parameters that studied were opening size, opening location, and the strengthening factor. Two deep beams were implemented as control specimens without opening and without strengthening. Eight deep beams were fabricated with openings but without strengthening, while

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Publication Date
Tue Feb 12 2019
Journal Name
Iraqi Journal Of Physics
Short-term effect of ultrasound therapy on stiffness elbow joint
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Elbow stiffness is hard to treat and commonly resulted from trauma or degenerative arthritis. This study aimed to demonstrate the effectiveness of using ultrasound therapy in management of stiff elbow joint resulted from several etiological factors. A total number of 42 patients (35 male and 7 female) allocated randomly from the Department of Physiotherapy at Al-yarmouk Teaching Hospital during 2013. Each patient examined physically by physiotherapist taking in consideration the measurement of the joint movement angle using goniometer in flexion and the extension, and the pain score using visual analogue scale (VAS). Ultrasound therapy initiated thrice weekly for two weeks. At the time of entry, the means degree of flexion and extension

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
Short Text Semantic Similarity Measurement Approach Based on Semantic Network
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Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, based on the words they share, do not perform well with short texts because two similar texts may be written in different terms by employing synonyms. As a result, short texts should be semantically compared. In this paper, a semantic similarity measurement method between texts is presented which combines knowledge-based and corpus-based semantic information to build a semantic network that repre

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Publication Date
Sat Apr 06 2019
Journal Name
International Journal Of English Linguistics
A Morpho- Syntactic study of Contemporary Science Fiction Short Stories
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The aim of the present study is to research two morphological processes: acronym and compounding (phrasal compounds/ circumlocution) and one syntactic category which are 'existential sentences' in science fiction short stories. The present paper identifies different types and rates of existential sentences. In this respect , 'bare existential and locative’ read the high percentages and may be contrasted with other classifications of English existential sentences which have a verb other than 'be' and a definite expression. 'Phrasal compounds' vary in rates as they constitute notable percentage for those that involve 'lexical means and lexical relations' followed by 'prepositional compounds' , 'conjunctional compounds' , and those invo

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Publication Date
Thu May 02 2024
Journal Name
Petroleum And Coal
Wellbore Instability Analysis to Determine the Failure Criteria for Deep Well/H Oilfield
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Cybersecurity And Information Management
Machine Learning-based Information Security Model for Botnet Detection
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Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Generative Adversarial Network for Imitation Learning from Single Demonstration
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Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

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Publication Date
Mon Jun 30 2025
Journal Name
Ingénierie Des Systèmes D Information
Comparative Analysis of Four Programming Languages for Machine Learning
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Publication Date
Mon Mar 14 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Mathematical simulation of memristive for classification in machine learning
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Publication Date
Thu Jun 17 2021
Journal Name
Revista Iberoamericana De PsicologÍa Del Ejercicio Y El Deporte
THE EFFECT OF USING THE ELECTRONIC PARTICIPATORY LEARNING STRATEGY ACCORDING TO THE WEB PROGRAMS IN LEARNING SOME BASIC SKILLS OF BASKETBALL FOR FIRST-GRADE INTERMEDIATE SCHOOL STUDENTS ACCORDING TO THE CURRICULAR COURSE
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The research aims to identify the impact of using the electronic participatory learning strategy according to internet programs in learning some basic basketball skills for middle first graders according to the curricular course, and the sample of research was selected in the deliberate way of students The first stage of intermediate school.As for the problem of research, the researchers said that there is a weakness in the levels of school students in terms of teaching basketball skills, which prompted the researchers to create appropriate solutions by using a participatory learning strategy.The researchers imposed statistically significant differences between pre and post-test tests, in favor of the post tests individually and in favor of

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