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Automatic Health Speech Prediction System Using Support Vector Machine

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Publication Date
Mon Oct 30 2023
Journal Name
Aro-the Scientific Journal Of Koya University
Enhancing Upper Limb Prosthetic Control in Amputees Using Non-invasive EEG and EMG Signals with Machine Learning Techniques

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Review of Smishing Detection Via Machine Learning

     Smishing is a cybercriminal attack targeting mobile Short Message Service (SMS) devices that contains a malicious link, phone number, or email. The attacker intends to use this message to steal the victim's sensitive information, such as passwords, bank account details, and credit cards. One method of combating smishing is to raise awareness and educate users about the various tactics used by SMS phishers. But even so, this method has been criticized for becoming inefficient because smishing tactics are continually evolving. A more promising anti-smishing method is to use machine learning. This paper introduces a number of machine learning algorithms that can be used for detecting smishing. Furthermore, the differences and simil

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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Publication Date
Sun Jan 01 2017
Journal Name
Ieee Access
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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Wallet Key Generation for a Generic Blockchain based on Speech

      As a new technology, blockchain provides the necessary capabilities to assure data integrity and data security through encryption. Mostly, all existing algorithms that provide security rely on the process of discovering a suitable key. Hence, key generation is considered the core of powerful encryption. This paper uses Zernike moment and Mersenne prime numbers to generate strong prime numbers by extracting the features from biometrics (speech). This proposed system sends these unique and strong prime numbers to the RSA algorithm to generate the keys. These keys represent a public address and a private key in a cryptocurrency wallet that is used to encrypt transactions. The benefit of this work is that it provides a high degree

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of The College Of Languages (jcl)
Areas in phonetics and phonology Differences Between Speech and Writing

In any language there is some amount of difference between written language (planned) and spoken language (spontaneous). Since planned speech could be considered a form of written language, it could be inferred that there are also differences between planned speech and spontaneous speech. Some of these differences are very clear in terms of syntax, lexis, phonology and discourse.  These differences are highlighted in order to make a clear distinction between spontaneous and planned speech.

             This paper is an attempt to show the differences between the two forms of a language (written & spoken English) as far as number of linguistic features are tackle

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Publication Date
Fri Aug 30 2019
Journal Name
Journal Of The College Of Education For Women
Men and Women’s Education and Illiteracy in Adrar Speech Community

In Algeria, education is compulsory for males and females. This foundational decision was taken right after the independence of the country in 1962. Soon after, in 1963, the central government decided the Arabisation of the whole educational levels starting from primary school till university. At the same period, illiteracy-eradication programmes were launched by the Ministry of Education to get rid of this post-colonial scourge. In the administrative department (or Wilaya) of Adrar, former Tuat, young males and females attend Quranic schools (Zawaya) well before any formal education, that is as early as 4-5 years of age. The adult people who are not enrolled in formal classes could sit for non-formal ones. However, actual measurements a

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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Subsurface 3D Prediction Porosity Model from Converted Seismic and Well Data Using Model Based Inversion Technique

Seismic inversion technique is applied to 3D seismic data to predict porosity property for carbonate Yamama Formation (Early Cretaceous) in an area located in southern Iraq. A workflow is designed to guide the manual procedure of inversion process. The inversion use a Model Based Inversion technique to convert 3D seismic data into 3D acoustic impedance depending on low frequency model and well data is the first step in the inversion with statistical control for each inversion stage. Then, training the 3D acoustic impedance volume, seismic data and porosity wells data with multi attribute transforms to find the best statistical attribute that is suitable to invert the point direct measurement of porosity from well to 3D porosity distribut

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Publication Date
Sun Jan 27 2019
Journal Name
Civil Engineering Journal
Prediction of Sediment Accumulation Model for Trunk Sewer Using Multiple Linear Regression and Neural Network Techniques

Sewer sediment deposition is an important aspect as it relates to several operational and environmental problems. It concerns municipalities as it affects the sewer system and contributes to sewer failure which has a catastrophic effect if happened in trunks or interceptors. Sewer rehabilitation is a costly process and complex in terms of choosing the method of rehabilitation and individual sewers to be rehabilitated.  For such a complex process, inspection techniques assist in the decision-making process; though, it may add to the total expenditure of the project as it requires special tools and trained personnel. For developing countries, Inspection could prohibit the rehabilitation proceeds. In this study, the researchers propos

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