scholarly journals Encapsulation Video Classification and Retrieval Based on Arabic Text

2021 ◽  
Vol 17 (4) ◽  
pp. 20-36
Author(s):  
Reem Aljorani ◽  
Boshra Zopon
Keyword(s):  
Classification Accuracy ◽  
Gradient Descent ◽  
Arabic Language ◽  
Stochastic Gradient Descent ◽  
Arabic Text ◽  
Video Classification ◽  
Search Technique ◽  
Cognitive Services ◽  
Audio Features ◽  
Educational Field

Since Arabic video classification is not a popular field and there isn’t a lot of researches in this area especially in the educational field. A system was proposed to solve this problem and to make the educational Arabic videos more available to the students. A survey was fulfilled to study several papers in order to design and implement a system that classifies videos operative in the Arabic language by extracting its audio features using azure cognitive services which produce text transcripts. Several preprocessing operations are then applied to process the text transcript. A stochastic gradient descent SGD algorithm was used to classify transcripts and give a suitable label for each video. In addition, a search technique was applied to enable students to retrieve the videos they need. The results showed that SGD algorithm recorded the highest classification accuracy with 89.3 % when compared to other learning models. In the section below, a survey was introduced consisting of the most relevant and recent papers to this work.

Taʾwīl and the Meaning of the Text in the Arabic Language: An Introduction to Understanding the Qur'an

2010 ◽  
Vol 12 (1-2) ◽  
pp. 337-314
Author(s):  
ʿAbd Allāh Muḥammad al-Shāmī
Keyword(s):  
Figurative Language ◽  
Arabic Language ◽  
Literary Text ◽  
Arabic Text ◽  
Comprehensive Understanding ◽  
Original Meaning ◽  
High Literature

The question of clarifying the meaning of a given Arabic text is a subtle one, especially as high literature texts can often be read in more than one way. Arabic is rich in figurative language and this can lead to variety in meaning, sometimes in ways that either adhere closely or diverge far from the ‘original’ meaning. In order to understand a fine literary text in Arabic, one must have a comprehensive understanding of the issue of taʾwīl, and the concept that multiplicity of meaning does not necessarily lead to contradiction. This article surveys the opinions of various literary critics and scholars of balāgha on this issue with a brief discussion of the concepts of tafsīr and sharḥ, which sometimes overlap with taʾwīl.

Comparison of SVM, RF and SGD Methods for Determination of Programmer's Performance Classification Model in Social Media Activities

2020 ◽  
Vol 4 (2) ◽  
pp. 329-335
Author(s):  
Rusydi Umar ◽  
Imam Riadi ◽  
Purwono
Keyword(s):  
Social Media ◽  
Gradient Descent ◽  
Classification Model ◽  
Stochastic Gradient Descent ◽  
Support Vector ◽  
Svm Algorithm ◽  
Vector Machines ◽  
Performance Patterns ◽  
A Company

The failure of most startups in Indonesia is caused by team performance that is not solid and competent. Programmers are an integral profession in a startup team. The development of social media can be used as a strategic tool for recruiting the best programmer candidates in a company. This strategic tool is in the form of an automatic classification system of social media posting from prospective programmers. The classification results are expected to be able to predict the performance patterns of each candidate with a predicate of good or bad performance. The classification method with the best accuracy needs to be chosen in order to get an effective strategic tool so that a comparison of several methods is needed. This study compares classification methods including the Support Vector Machines (SVM) algorithm, Random Forest (RF) and Stochastic Gradient Descent (SGD). The classification results show the percentage of accuracy with k = 10 cross validation for the SVM algorithm reaches 81.3%, RF at 74.4%, and SGD at 80.1% so that the SVM method is chosen as a model of programmer performance classification on social media activities.

Cloning Safe Driving Behavior for Self-Driving Cars using Convolutional Neural Networks

2019 ◽  
Vol 12 (2) ◽  
pp. 120-127 ◽  
Author(s):  
Wael Farag
Keyword(s):  
Gradient Descent ◽  
Autonomous Driving ◽  
Driving Behavior ◽  
Training Data ◽  
Stochastic Gradient Descent ◽  
Data Set ◽  
Safe Driving ◽  
Processing Pipeline ◽  
Self Driving Cars ◽  
And Training

Background: In this paper, a Convolutional Neural Network (CNN) to learn safe driving behavior and smooth steering manoeuvring, is proposed as an empowerment of autonomous driving technologies. The training data is collected from a front-facing camera and the steering commands issued by an experienced driver driving in traffic as well as urban roads. Methods: This data is then used to train the proposed CNN to facilitate what it is called “Behavioral Cloning”. The proposed Behavior Cloning CNN is named as “BCNet”, and its deep seventeen-layer architecture has been selected after extensive trials. The BCNet got trained using Adam’s optimization algorithm as a variant of the Stochastic Gradient Descent (SGD) technique. Results: The paper goes through the development and training process in details and shows the image processing pipeline harnessed in the development. Conclusion: The proposed approach proved successful in cloning the driving behavior embedded in the training data set after extensive simulations.

scholarly journals Revisiting the dynamic interactions between economic growth and environmental pollution in Italy: evidence from a gradient descent algorithm

2021 ◽  
Author(s):  
Marco Mele ◽  
Cosimo Magazzino ◽  
Nicolas Schneider ◽  
Floriana Nicolai
Keyword(s):  
Economic Growth ◽  
Gradient Descent ◽  
Statistical Data ◽  
Stochastic Gradient Descent ◽  
Policy Recommendations ◽  
Dynamic Interactions ◽  
Gradient Descent Algorithm ◽  
The Relationship ◽  
Main Strand ◽  
Yearly Data

AbstractAlthough the literature on the relationship between economic growth and CO2 emissions is extensive, the use of machine learning (ML) tools remains seminal. In this paper, we assess this nexus for Italy using innovative algorithms, with yearly data for the 1960–2017 period. We develop three distinct models: the batch gradient descent (BGD), the stochastic gradient descent (SGD), and the multilayer perceptron (MLP). Despite the phase of low Italian economic growth, results reveal that CO2 emissions increased in the predicting model. Compared to the observed statistical data, the algorithm shows a correlation between low growth and higher CO2 increase, which contradicts the main strand of literature. Based on this outcome, adequate policy recommendations are provided.

scholarly journals A Comparative Analysis of Arabic Text Steganography

2021 ◽  
Vol 11 (15) ◽  
pp. 6851
Author(s):  
Reema Thabit ◽  
Nur Izura Udzir ◽  
Sharifah Md Yasin ◽  
Aziah Asmawi ◽  
Nuur Alifah Roslan ◽  
...  
Keyword(s):  
Evaluation Criteria ◽  
Arabic Language ◽  
Text Messages ◽  
Secret Message ◽  
Sensitive Information ◽  
Arabic Text ◽  
Ideal Object ◽  
Internet Users ◽  
Text Steganography ◽  
Text Content

Protecting sensitive information transmitted via public channels is a significant issue faced by governments, militaries, organizations, and individuals. Steganography protects the secret information by concealing it in a transferred object such as video, audio, image, text, network, or DNA. As text uses low bandwidth, it is commonly used by Internet users in their daily activities, resulting a vast amount of text messages sent daily as social media posts and documents. Accordingly, text is the ideal object to be used in steganography, since hiding a secret message in a text makes it difficult for the attacker to detect the hidden message among the massive text content on the Internet. Language’s characteristics are utilized in text steganography. Despite the richness of the Arabic language in linguistic characteristics, only a few studies have been conducted in Arabic text steganography. To draw further attention to Arabic text steganography prospects, this paper reviews the classifications of these methods from its inception. For analysis, this paper presents a comprehensive study based on the key evaluation criteria (i.e., capacity, invisibility, robustness, and security). It opens new areas for further research based on the trends in this field.

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