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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 Jun 01 2007
Journal Name
Journal Of Al-nahrain University Science
ON THE GREEDY RADIAL BASIS FUNCTION NEURAL NETWORKS FOR APPROXIMATION MULTIDIMENSIONAL FUNCTIONS
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The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Improving IoT Applications Using a Proposed Routing Protocol
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The main objective of this work is to propose a new routing protocol for wireless sensor network employed to serve IoT systems. The routing protocol has to adapt with different requirements in order to enhance the performance of IoT applications. The link quality, node depth and energy are used as metrics to make routing decisions. Comparison with other protocols is essential to show the improvements achieved by this work, thus protocols designed to serve the same purpose such as AODV, REL and LABILE are chosen to compare the proposed routing protocol with. To add integrative and holistic, some of important features are added and tested such as actuating and mobility. These features are greatly required by some of IoT applications and im

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Publication Date
Sun Mar 06 2011
Journal Name
Baghdad Science Journal
Measuring Uranium in the Soil of Some Area in Missan Governorate/ Iraq
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Concentrations of uranium were measured in this study for twenty soil samples from four areas with different depths (soil surface-20-40-60-80)cm .The study regions include Missan Governorate (Al-Iskan area,Al-Shibbana area ,Hai-Al Moualimin Al Jadied area ,Sector 30 area). The Uranium concentrations in soil samples measured by using fission tracks registration in (CR-39) track detector that caused by the bombardment of (U-283) with thermal neutrons from (241Am-Be) neutron source that has flux neutron thermal of (5 ×103 n cm-2 s-1). The concentrations values were calculated by a comparison with standard samples. Through out the result, it was found that averages of uranium concentrations in soil samples were as the following : Al - Iskan

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Publication Date
Wed Aug 17 2022
Journal Name
Aip Conference Proceedings
The effect of using Gaussian, Kurtosis and LogCosh as kernels in ICA on the satellite classification accuracy
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This study focusses on the effect of using ICA transform on the classification accuracy of satellite images using the maximum likelihood classifier. The study area represents an agricultural area north of the capital Baghdad - Iraq, as it was captured by the Landsat 8 satellite on 12 January 2021, where the bands of the OLI sensor were used. A field visit was made to a variety of classes that represent the landcover of the study area and the geographical location of these classes was recorded. Gaussian, Kurtosis, and LogCosh kernels were used to perform the ICA transform of the OLI Landsat 8 image. Different training sets were made for each of the ICA and Landsat 8 images separately that used in the classification phase, and used to calcula

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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Publication Date
Tue Jan 07 2020
Journal Name
Xi,an University Of Architecture &technology
The Effect of Jigsaw strategy on Academic Achievement and Engagement in Learning among the 3rd male graders students in Chemistry
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The research aims to identify the effect of jigsaw strategy in learning achievement and engaging for the third grade intermediate students in chemistry. The research sample consisted of (61) students distributed in two experimental and control groups. The research tools consisted in the achievement test and the measure of engaging learning. The results showed that there are statistically significant differences at the level of (α = 0.05) between the experimental group and the control group in both the achievement test and the measure of learning involvement for the benefit of the experimental group. In this light, the researcher recommended the use of jigsaw strategy for teaching the subject matter. Lamia because of its impact in raising

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Publication Date
Fri Dec 31 2021
Journal Name
Iraqi Journal Of Laser
The influence of no-core fibre length on the sensitivity Optical fibre Humidity sensor
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Abstract: Reflection optical fibre Humidity sensor is presented in this work, which is based on no core fibre prepared by splicing a segment of no core fibre (NCF) at different lengths 1-6 cm with fixed diameter 125 µm and a single mode fibre (SMF). The range of humidity inside the chamber is controlled from 30% to 90% RH at temperature ~ 30 °С. The experimental result shows that the resonant wavelength dip shift decreases linearly with an increment of RH% and the sensitivity of the sensor increased linearly with an increasing in the length of NCF. However, a high sensitivity 716.07pm/RH% is obtained at length 5cm with good stability and reputability.  Furthermore, the sensor is shif

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Publication Date
Thu Nov 13 2025
Journal Name
Wasit Journal Of Sports Sciences
The effect of RTX traning and plastic hurdles on some kinematic variables and learning the performance of the event of 100 mH for female students
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Publication Date
Sun Aug 28 2022
Journal Name
Geodesy And Cartography
OBJECT-BASED APPROACHES FOR LAND USE-LAND COVER CLASSIFICATION USING HIGH RESOLUTION QUICK BIRD SATELLITE IMAGERY (A CASE STUDY: KERBELA, IRAQ)
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Land Use / Land Cover (LULC) classification is considered one of the basic tasks that decision makers and map makers rely on to evaluate the infrastructure, using different types of satellite data, despite the large spectral difference or overlap in the spectra in the same land cover in addition to the problem of aberration and the degree of inclination of the images that may be negatively affect rating performance. The main objective of this study is to develop a working method for classifying the land cover using high-resolution satellite images using object based method. Maximum likelihood pixel based supervised as well as object approaches were examined on QuickBird satellite image in Karbala, Iraq. This study illustrated that

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Publication Date
Thu Jan 04 2024
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Impact of Performance Auditing Process Pursuant to the Programs and Policies Guide in improving the health insurance Prosperity: applied research in the Iraqi General Insurance Company
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Abstract

              The research’s goal lies in demonstrating the impact of the Federal Financial Supervision Endowment through the process of auditing the performance of the entities subject to its audit as to improve the performance of these entities, especially if the performance audit method is one of the newly applied methods that are compatible with the standards issued by the International Organization of Financial Supervision and Accounting Institutions which is the method of auditing performance according to the performance evaluation guide for programs and policies issued by the Federal Office of Financial Supervision.

 T

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