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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
Mon Jan 01 2024
Journal Name
2nd International Conference For Engineering Sciences And Information Technology (esit 2022): Esit2022 Conference Proceedings
ZnO nanostructures as low concentration NO2 gas sensor and impact the temperature on sensing properties
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Zinc oxide (ZnO) nanostructures were synthesized through the hydrothermal method at various conditions growth times (6,7 and 8 hrs.) and a growth temperature (70, 90, and 100 ºC). The prepared ZnO nanostructure samples were described using scanning electron microscopy (SEM) and X-ray diffractometer to distinguish their surface morphologies and crystal structures. The ZnO samples were confirmed to have the same crystal type, with different densities and dimensions (diameter and length). The obtained ZnO nanostructures were used to manufacture gas sensors for NO2 gas detection. Sensing characteristics for the fabricated sensor to NO2 gas were examined at different operating temperatures (180, 200, 220, and 240) ºC with a low gas concentrati

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Publication Date
Tue Sep 01 2020
Journal Name
Optik
Synthesis of Ag2O films by pulsed laser deposited on porous silicon as gas sensor application
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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Petrophysical Properties of Khasib Formation in East Baghdad Oil Field Southern Area
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Petrophysical properties evaluation from well log analysis has always been crucial for the identification and assessment of hydrocarbon bearing zones. East Baghdad field is located 10 km east of Baghdad city, where the southern area includes the two southern portions of the field, Khasib formation is the main reservoir of East Baghdad oil field.

In this paper, well log data of nine wells have been environmentally corrected, where the corrected data used to determine lithology, shale volume, porosity, and water saturation. Lithology identified by two methods; neutron-density and M-N matrix plots, while the shale volume estimated by single shale indicator and dual shale indicator, The porosity is calculated from the three common po

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Publication Date
Mon May 21 2007
Journal Name
Journal Of Planner And Development
The Efficiency of the Distribution for Educational Services in Al-Athamiyah area
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The educational service one of activities which have great effect in the city life and it's community which considered as an affective instrument for the social and civilized construction and its role in the development of culture and determining the general features of the society. Therefore planning for educational service is considered as a necessary for economical, social and cultural conditions in the Arab community lives in general and the Iraqi community in special. The educational service buildings and distribution forms an insurmountable obstacle in the urban areas. So the balance distribution in Baghdad presents an indication to ensure the equality of educational opportunities besides the correlation of these institutes with th

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Using Fuzzy Clustering to Detect the Tumor Area in Stomach Medical Images
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Although the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
The Effect of Vehicle Body Shapes on the Near Wake Region and Drag Coefficient: A Numerical Study
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The purpose of this paper is to gain a good understanding about wake region behind the car body due to the aerodynamic effect when the air flows over the road vehicle during its movement. The main goal of this study is to discuss the effect of the geometry on the wake region and the aerodynamic drag coefficient. Results will be achieved by using two different shapes, which are the fastback and the notchback. The study will be implemented by the Computational Fluid Dynamic (CFD) by using STAR-CCM+® software for the simulation. This study investigates the steady turbulent flow using k-epsilon turbulence model. The results obtained from the simulation show that the region of the air separation behind the vehicle

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
The Impact of Six Thinking Hats Strategy on Improving Creative Thinking Skills" Field research in the Medical City "
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Abstract  

   The research problem focuses on studying the interest of the Medical City Department of the Ministry of Health in improving the creative thinking skills of the administrative leadership through parallel & comprehensive thinking according to the of six thinking hats strategy. The research sample consisted of (170) administrative leaders in the upper & middle organizational levels, The questionnaire was used as a main tool for data collection, In addition to the observation & Interview, The research sought to answer the following questions: What is the extent to which the administrative leadership (Tpp & middle) in the organization investigated the concept of the six thinkin

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Publication Date
Wed Nov 01 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Protective Effect of Daidzein on Ifosfamide-Induced Neurotoxicity Via Improving Some Selected Oxidative Stress Parameters in Male Rats
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  In this study, the possible protective effects of daidzein on ifosfamide-induced neurotoxicity in male rats were examined by the determination of changes in selected oxidant–antioxidant markers of male rats’ brain tissue.

Twenty-eight (28) apparently-healthy Wistar male rats weighing (120-150gm) allocated into 4 groups (n=7) were used in this study. Rats orally-administered 1% tween 20 dissolved in distilled water/Control (Group I); rats were orally-administered daidzein suspension (100mg/kg) for 7 days (Group II); rats intraperitoneally-injected with a single dose of ifosfamide (500 mg/kg) (Group III); rats orally-administered for 7 days with the daidzein (100mg/

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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