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.
In this work, the circular patch antenna was fabricated and analyzed. Microwave Studio (version 2019) computer simulation technology (CST) was used to design the circular patch antenna. The material FR-4 was used to build this antenna, using the computer numerical control (CNC) method to implement this work. For the purpose of accomplishing this design, the values of the resonant frequency, dielectric constant and dielectric thickness of the material used as in 4.424, 2.4 GHz and 0.159 cm respectively were used as inputs to the CST program to get the said program outputs for the required antenna radius with the logarithmic function (F) of the circular patch antenna 1.6909 cm and 1.7415 cm respectively. Practically, the b
... Show MoreThe performance of photovoltaic (PV) panel having staggered metal foam fins was examined experimentally in Baghdad, Iraq. Three staggered metal foam fin configurations attached to the backside of the PV panel were studied. The measured parameters were front and back surfaces temperature, open voltage and current circuits, maximum power, and PV efficiency. It was noted that the maximum electrical efficiency enhancement was 4.7% for staggered metal foam fins (case III) than the reference PV panel. The operating temperature of the cell was increased when the value of solar intensity was high. Thereby, the electrical efficiency was decreased. It was found that the metal foam fins decreased the PV temperature by 2-3 o
... Show MoreThis study aimed to identify the political factors influencing the performance of specialized journalists in Iraqi electronic newspapers. The significance of the study stems from the role of communication in newspapers that have established themselves in reality due to their wide dissemination, multiple uses, expanding freedom base, and the current diversity in perspectives. These newspapers highlight and publish societal issues of concern. The importance of these newspapers is associated with their creators who face various factors affecting their value and performance, whether positively or negatively. In light of this, the political factor was identified as the primary driver for other influencing factors. The
... Show MoreThis study introduces a series of single and pile group model tests subjected to lateral loads in . multilayered sand from Karbala, Iraq. The aim of this study is to investigate: the performance of the pile groups subjected to lateral loads; in which the pile batter inclination angle is changed; the effect of pile spacing (s/d) ratio, the influence of using different number of piles and pile group configuration. Results revealed that the performance of single negative (Reverse) Battered piles with inclination of 10° and 20° show a gain of 32% and 76 % in the ultimate lateral capacity over the regular ones. For pile groups, the use of a combination of regular, negative and positive battered piles in
... Show MoreIn this paper, we investigate and characterize the effects of multi-channel and rendezvous protocols on the connectivity of dynamic spectrum access networks using percolation theory. In particular, we focus on the scenario where the secondary nodes have plenty of vacant channels to choose from a phenomenon which we define as channel abundance. To cope with the existence of multi-channel, we use two types of rendezvous protocols: naive ones which do not guarantee a common channel and advanced ones which do. We show that, with more channel abundance, even with the use of either type of rendezvous protocols, it becomes difficult for two nodes to agree on a common channel, thereby, potentially remaining invisible to each other. We model this in
... Show MoreThe speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T
In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained
Nowadays, the mobile communication networks have become a consistent part of our everyday life by transforming huge amount of data through communicating devices, that leads to new challenges. According to the Cisco Networking Index, more than 29.3 billion networked devices will be connected to the network during the year 2023. It is obvious that the existing infrastructures in current networks will not be able to support all the generated data due to the bandwidth limits, processing and transmission overhead. To cope with these issues, future mobile communication networks must achieve high requirements to reduce the amount of transferred data, decrease latency and computation costs. One of the essential challenging tasks in this subject
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