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ijs-4039
Word Embedding Methods for Word Representation in Deep Learning for Natural Language Processing
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    Natural Language Processing (NLP) deals with analysing, understanding and generating languages likes human. One of the challenges of NLP is training computers to understand the way of learning and using a language as human.  Every training session consists of several types of sentences with different context and linguistic structures. Meaning of a sentence depends on actual meaning of main words with their correct positions. Same word can be used as a noun or adjective or others based on their position. In NLP, Word Embedding is a powerful method which is trained on large collection of texts and encoded general semantic and syntactic information of words. Choosing a right word embedding generates more efficient result than others. Most of the papers used pretrained word embedding vector in deep learning for NLP processing. But, the major issue of pretrained word embedding vector is that it can’t use for all types of NLP processing. In this paper, a local word embedding vector formation process have been proposed and shown a comparison between pretrained and local word embedding vectors for Bengali language. The Keras framework is used in Python for local word embedding implementation and analysis section of this paper shows proposed model produced 87.84% accuracy result which is better than fastText pretrained word embedding vectors accuracy 86.75%. Using this proposed method NLP researchers of Bengali language can easily build the specific word embedding vectors for word representation in Natural Language Processing.

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Publication Date
Sun Sep 27 2020
Journal Name
Journal Of The College Of Education For Women
Feminization and Masculinization of the Word Sun in the Holy Quran: A Semantic Study
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It is no secret for those concerned with language concerns that the issue of figurative feminization is one of the issues that does not follow a grammatical rule governed by the fact that the subject of knowledge of this is due to hearing as indicated by linguistic references and lexicons.This research opts to find out the origin of the feminization of the word sun in the Arabic language and in light of what some language specialists have argued that the origin of figurative feminization was due to non-linguistic motives related to religious and metaphysical beliefs, and that it was memory preserved in light of the linguistic heritage.The research concluded that the feminization of the sun goes back to what settled in their minds, which

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Publication Date
Wed Mar 15 2023
Journal Name
International Journal Of Advances In Intelligent Informatics
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-Jone

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Publication Date
Thu Dec 16 2021
Journal Name
Translational Vision Science & Technology
A Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps
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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
ORGANIZATION OF MEMORY CHIPS IN MEMORY SYSTEMS THAT HAVE WORD SIZE WIDER THAN 8-BIT
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This paper presents a method to organize memory chips when they are used to build memory systems that have word size wider than 8-bit. Most memory chips have 8-bit word size. When the memory system has to be built from several memory chips of various sizes, this method gives all possible organizations of these chips in the memory system. This paper also suggests a precise definition of the term “memory bank” that is usually used in memory systems. Finally, an illustrative design problem was taken to illustrate the presented method practically.

Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Engineering
ORGANIZATION OF MEMORY CHIPS IN MEMORY SYSTEMS THAT HAVE WORD SIZE WIDER THAN 8-BIT
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This paper presents a method to organize memory chips when they are used to build memory systems that have word size wider than 8-bit. Most memory chips have 8-bit word size. When the memory system has to be built from several memory chips of various sizes, this method gives all possible organizations of these chips in the memory system. This paper also suggests a precise definition of the term “memory bank” that is usually used in memory systems. Finally, an illustrative design problem was taken to illustrate the presented method practically

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Publication Date
Mon Dec 26 2022
Journal Name
Journal Of The College Of Languages (jcl)
Word-Formation Motivation of Diminutive Vocabulary in Russian and Arabic: Словообразовательная мотивация диминутивной лексики в русском и арабском языках
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The question of word–formation motivation is one of the most urgent problems of morphological features of diminutive vocabulary in the languages of different structures, Arabic – Semitic and Russian - Slavic. The relevance of this question lies in the fact that the analysis of morphological elements of word-formation motivation plays an important role not only in identifying formal and semantic connections between different units of the same language, but also has an applied value in the comparative study of different languages. Taking in to account that word-formation motivation is usually considered sequentially in order to identify motivational relationships of this type of vocabulary, we will study motivation in comparative analy

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Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
Diabetes Diagnosis Using Deep Learning
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     Hyperglycemia is a complication of diabetes (high blood sugar). This condition causes biochemical alterations in the cells of the body, which may lead to structural and functional problems throughout the body, including the eye. Diabetes retinopathy (DR) is a type of retinal degeneration induced by long-term diabetes that may lead to blindness. propose our deep learning method for the early detection of retinopathy using an efficient net B1 model and using the APTOS 2019 dataset. we used the Gaussian filter as one of the most significant image-processing algorithms. It recognizes edges in the dataset and reduces superfluous noise. We will enlarge the retina picture to 224×224 (the Efficient Net B1 standard) and utilize data aug

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Publication Date
Sun Oct 03 2021
Journal Name
Rudn Journal Of Language Studies, Semiotics And Semantics
Motivation of Word Formation in Russian and Arabic Languages and its Role in Achieving Translation Equivalence
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The article is devoted to the issue of word-formation motivation, which does not lose its relevance and plays a role not only in disclosing formal-semantic relations between words of one language and has not only theoretical, but also applied significance. The authors consider word-formation motivation consistently in its varieties in a comparative way on the materials of so different languages as Russian and Arabic and approach the mechanism of achieving semantic equivalence of translation. To the greatest extent, word-formation activity today, due to objective reasons, affects some special branch (technical, medical, etc.) vocabulary, which is increasing from year to year in national dictionaries. This extensive material, selected

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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
A modified Mobilenetv2 architecture for fire detection systems in open areas by deep learning
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This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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