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Selecting the optimal movement subset with different pattern recognition based EMG control algorithms
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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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Publication Date
Wed Aug 01 2018
Journal Name
Engineering And Technology Journal
A Proposed Method for the Sound Recognition Process
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Publication Date
Wed Jun 01 2016
Journal Name
Ieee Transactions On Neural Systems And Rehabilitation Engineering
Improving the Performance Against Force Variation of EMG Controlled Multifunctional Upper-Limb Prostheses for Transradial Amputees
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Publication Date
Tue Aug 20 2019
Journal Name
Political Sciences Journal
Moved movement the dynamics of conflict and the restructuring of balance maps in Syria
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This study deals with the absence of state control over the whole of the Syrian geography in creating an environment conducive to the emergence of a new force represented by armed groups and organizations that point to fundamental changes in the conflict and to transform competition for control over the land into a struggle for influence. Which in itself represents the prospects of change in the Syrian scene, and that understanding their interests requires shedding light on the extent of the continuation of this competition and the conflict on land and expansion at the expense of the other, and thus contribute to complicate the Syrian scene, especially after attempts to bite Of land and annexation to each party's areas of influence, espe

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Publication Date
Fri Jun 29 2018
Journal Name
Journal Of The College Of Education For Women
HandWritten Numerals Recognition System
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  Recognition is one of the basic characteristics of human brain, and also for the living   creatures. It is possible to recognize images, persons, or patterns according to their characteristics. This recognition could be done using eyes or dedicated proposed methods. There are numerous applications for pattern recognition such as recognition of printed or handwritten letters, for example reading post addresses automatically and reading documents or check reading in bank.

      One of the challenges which faces researchers in character recognition field is the recognition of digits, which are written by hand. This paper describes a classification method for on-line handwrit

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Publication Date
Sat Jun 01 2013
Journal Name
مجلة كلية بغداد للعلوم الاقتصادية الجامعة
Proposed family speech recognition
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Speech recognition is a very important field that can be used in many applications such as controlling to protect area, banking, transaction over telephone network database access service, voice email, investigations, House controlling and management ... etc. Speech recognition systems can be used in two modes: to identify a particular person or to verify a person’s claimed identity. The family speaker recognition is a modern field in the speaker recognition. Many family speakers have similarity in the characteristics and hard to identify between them. Today, the scope of speech recognition is limited to speech collected from cooperative users in real world office environments and without adverse microphone or channel impairments.

Publication Date
Wed Apr 05 2023
Journal Name
Journal Of Engineering
A Developed Model for Selecting Optimum Locations of Water Harvesting Dams Using GIS Techniques
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An integrated GIS-VBA (Geographical Information System – Visual Basic for Application), model is developed for selecting an optimum water harvesting dam location among an available locations in a watershed. The proposed model allows quick and precise estimation of an adopted weighted objective function for each selected location. In addition to that for each location, a different dam height is used as a nominee for optimum selection. The VBA model includes an optimization model with a weighted objective function that includes beneficiary items (positive) , such as the available storage , the dam height allowed by the site as an indicator for the potential of hydroelectric power generation , the rainfall rate as a source of water . In a

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
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Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
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Publication Date
Mon Dec 01 2014
Journal Name
Advances In Engineering Software
System identification and control of robot manipulator based on fuzzy adaptive differential evolution algorithm
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Publication Date
Tue Apr 02 2024
Journal Name
Engineering, Technology &amp; Applied Science Research
Two Proposed Models for Face Recognition: Achieving High Accuracy and Speed with Artificial Intelligence
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In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

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