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Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two supervised machine learning classification techniques, Learning Vector Quantization (LVQ) and Support Vector Machine (SVM) classifiers, to achieve better search performance and high classification accuracy in a heterogeneous WBASN. These classification techniques are responsible for categorizing each incoming packet into normal, critical, or very critical, depending on the patient's condition, so that any problem affecting him can be addressed promptly. Comparative analyses reveal that LVQ outperforms SVM in terms of accuracy at 91.45% and 80%, respectively.

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Publication Date
Fri Jul 26 2024
Journal Name
Academia Open
Enhancing Pediatric Nursing Skills by Top Learning Strategies
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Background: The efficacy of educational strategies is crucial for nursing students to competently perform pediatric procedures like nasogastric tube insertion. Specific Background: This study evaluates the effectiveness of simulation, blended, and self-directed learning strategies in enhancing these skills among nursing students. Knowledge Gap: Previous research lacks a comprehensive comparison of these strategies' impacts on skill development in pediatric nursing contexts. Aims: The study aims to assess the effectiveness of different educational strategies on nursing students' ability to perform pediatric nasogastric tube insertions. Methods: A pre-experimental design was employed at the College of Nursing, University of Baghdad, i

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Publication Date
Fri Mar 18 2022
Journal Name
Aro-the Scientific Journal Of Koya University
Detecting Deepfakes with Deep Learning and Gabor Filters
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The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Engineering
Iraqi Sentiment and Emotion Analysis Using Deep Learning
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Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

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Publication Date
Tue Dec 21 2021
Journal Name
Mendel
Hybrid Deep Learning Model for Singing Voice Separation
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Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

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Publication Date
Mon Feb 19 2018
Journal Name
Al-academy
Performance of the comedian in Moliere plays
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This research aims to study the performance of comedian in the plays of writer Moliere . The problem of research is to answer the following question:      How does comedian Moliere's techniques in a number of his plays and funny acts?   The    research aims at revealing the means used by the comedian in his performance of a comedic character in the number of Moliere plays.                                                 

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Publication Date
Fri Mar 25 2022
Journal Name
Journal Of The College Of Basic Education
Semantic image coding in contemporary Theatrical performance
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تعد مجالات الصورة وعلاماتها الحركية حضوراً دلالياً للاتصال العلامي واتساعاً في الرابطة الجدلية ما بين الدوال ومداليها، التي تقوم بها الرؤية الاخراجية لإنتاج دلالات اخفائية تمتلك جوهرها الانتقالي عبر الافكار بوصفها معطيات العرض، ويسعى التشفير الصوري الى بث ثنائية المعنى داخل الحقول المتعددة للعرض المسرحي، ولفهم المعنى المنبثق من هذه التشفيرات البصرية، تولدت الحاجة لبحث تشكيل هذه التشفيرات وكيفية تح

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Publication Date
Tue Dec 23 2025
Journal Name
Sciences Journal Of Physical Education
Using two types of electronic questions by applying the Quiz Creator program in the method of guided discovery and its effect on learning and maintaining a motor chain on the throat
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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
The role of marketing recovery in improving the organization's reputation An applied study of a sample of private bank managers in Baghdad
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This research aims to know and the role of the marketing recovery dimensions in improving the organization's reputation through an exploratory study of private banks in the city of Baghdad. The aim of the research is to define the role of the marketing recovery through its dimensions (compensation, apology, speed of response, assistance and problem solving), in improving the organization's reputation, as the research will attempt to provide a theoretical framework for the dimensions studied through the most important of what researchers presented and then conduct the applied aspect of the research. Data were collected using a questionnaire-based survey consisting of 35 questions and distributed to 110 managers of private banks in

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Publication Date
Wed Sep 21 2022
Journal Name
Journal Of Planner And Development
The role of municipal councils in achieving and localizing sustainable development in the local community (The municipality of Al-Shafa area in Ajloun governorate in Jordan as a model)
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Ajloun Governorate is considered the smallest governorate in Jordan in terms of area, and its population density rises to 472.2 people/ km2 and is distributed among five municipalities. The Al-Shafa municipality is one of these municipalities. Al-Shafa is rich in its natural and human resources, and the first municipal council was established in it in 2001.

This study seeks to achieve the following general objective: inventory the natural and human resources that Al-Shafa enjoys, and highlight the role of Al-Shafa municipality in achieving and settling sustainable development for the local community. Certain content, which are: the comprehensive approach to geographical reality, the descriptive

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Publication Date
Thu Dec 01 2016
Journal Name
Al.qadisiya Journal For The Sciences Of Physical Education
Comparing self-learning associated with the model and learning reverse fashioned way of partial way to learn Olympic lifts for beginners
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Abstract The purpose of this study, teach the art of performing Olympic lifts (snatch and, clean and jerk) using the two methods are instructional (self-learning associated with the model) and (reverse style of partial way). Identify the effectiveness of these methods in learning the art of performance and style of the best Olympic lifting in the learning and retention of novice for Olympic lifts. The research sample consisted of 16 lifters were selected purposively representing specialist center for the care of athletic talent to weightlifting for ages 14 years. The sample was divided into two experimental, Each group (8) eight weightlifters. The experimental group used the style of the first self-learning associated with the m

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