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.
The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge
... Show MoreThis 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
... Show MoreBackground: Hair loss is a common distressing disease and challenging problem for many dermatologist. Telogen effluvium is the most common hair loss disease in which nutritional deficiencies may precipitate the disease through their effect on hair structure and growth.
Study Aim : Validating role of serum ferritin level and body mass index in Chronic Telogen Effluvium and analyzing association between these factors with socioeconomic, demographic, gynecological factors and weight loss effect. Establishing a nutritional preventive advice to improve treatment successfulness and decrease the disease occurrence.
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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
... Show MoreThis study has dealt with, the issue of classification of rural road network , in addition to prepare a suggested for the classification for this network in Iraq , this classification account , the specifications and characteristics of rural roads, population, and the range taking of settlements , then this classification was applied on the rural road network in the Najaf province there are four categories of classification ,the first is major arterial rural roads divided into two major arterial and minor arterial roads , while the second category collected roads which was divided into minor arterial roads and main collected roads. The third category was represented by Local Roads , it has been divided into paved roads and unpaved, the f
... Show MoreConcentrations 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
... Show MoreBackground: Non-alcoholic fatty liver disease (NAFLD) is the most common liver disorder globally. The prevalence is 25% worldwide, distributed widely in different populations and regions. The highest rates are reported for the Middle East (32%). Due to modern lifestyles and diet, there has been a persistent increase in the number of NAFLD patients. This increase occurred at the same time where there were also increases in the number of people considered being obese all over the world. By analyzing fatty liver risk factors, studies found that body mass index, one of the most classical epidemiological indexes assessing obesity, was associated with the risk of fatty liver.
Objectives: To assess age, sex, and body
... Show MoreThe 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]).
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
... Show MoreThe 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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