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An efficient node selection algorithm in the context of IoT-based vehicular ad hoc network for emergency service
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Abstract<p>With the recent growth of global populations, main roads in cities have witnessed an evident increase in the number of vehicles. This has led to unprecedented challenges for authorities in managing the traffic of ambulance vehicles to provide medical services in emergency cases. Despite the high technologies associated with medical tracks and advanced traffic management systems, there is still a current delay in ambulances’ attendance in times of emergency to provide patients with vital aid. Therefore, it is indispensable to introduce a new emergency service system that enables the ambulance to reach the patient in the least congested and shortest paths. However, designing an efficient algorithm to plan the best route for an ambulance is still a global goal and a challenge that needs to be solved. This article introduces an Internet of Things emergency services system based on a real-time node rank index (NR-index) algorithm to find the best route for the ambulance to reach the patient and provide the required medical services in emergency cases. The proposed system design copes with the dynamic traffic conditions to guarantee the shortest transport time. For this purpose, a vehicular ad hoc network is employed to collect accurate real-time traffic data. In this article, we suggest two parameters to compromise distance and congestion level. The first is the distance between the patient and the surrounding ambulance vehicles, and the second determines the congestion level to avoid the path with high congestion traffic. The system employs a developed real-time NR-index algorithm to select a suitable ambulance vehicle to respond to emergency cases at a low travel cost with the fastest journey. Finally, our system makes it easier for ambulance vehicles to use the best route and avoid heavy traffic. This allows them to make their way to the patient quickly and increases the chance of saving lives. The simulation results show significant improvements in terms of average travel time, average travel speed, and normalized routing load.</p>
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Publication Date
Sun Mar 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Characterization of nickel oxide nanocatalyst electrodes for an alkaline fuel cell
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Abstract<p>In this paper had been studied the characterization of the nanocatalyst (NiO) Mesh electrodes. For fuel cell. The catalyst is prepared and also the electrodes The structural were studied through the analysis of X-ray diffraction of the prepared nanocatalyst for determining the yielding phase and atomic force microscope to identify the roughness of prepared catalyst surface, Use has been nanocatalyst led to optimization of cell voltage, current densities & power for a fuel cell.</p>
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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Simulation Recording of an ECG, PCG, and PPG for Feature Extractions
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Recently, the development of the field of biomedical engineering has led to a renewed interest in detection of several events. In this paper a new approach used to detect specific parameter and relations between three biomedical signals that used in clinical diagnosis. These include the phonocardiography (PCG), electrocardiography (ECG) and photoplethysmography (PPG) or sometimes it called the carotid pulse related to the position of electrode.

Comparisons between three cases (two normal cases and one abnormal case) are used to indicate the delay that may occurred due to the deficiency of the cardiac muscle or valve in an abnormal case.

The results shown that S1 and S2, first and second sound of the

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Publication Date
Sat Feb 09 2019
Journal Name
Iraqi Journal Of Laser
Reconstruction of 3D Shape for an Object using Laser Scanning Triangulation
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This paper presents a method of designing and constructing a system capable of acquiring
the third dimension and reconstructs a 3D shape for an object from multi images of that object using
the principle of active optical triangulation. The system consists of an illumination source, a photo
detector, a movement mechanism and a PC, which is working as a controlling unit for the hard ware
components and as an image processing unit for the object multi view raw images which must be
processed to extract the third dimension. The result showed that the optical triangulation method
provides a rapid mean for obtaining accurate and quantitative distance measurements. The final
result's analysis refers to the necessity of usin

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Hiding the Type of Skin Texture in Mice based on Fuzzy Clustering Technique
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A substantial matter to confidential messages' interchange through the internet is transmission of information safely. For example, digital products' consumers and producers are keen for knowing those products are genuine and must be distinguished from worthless products. Encryption's science can be defined as the technique to embed the data in an images file, audio or videos in a style which should be met the safety requirements. Steganography is a portion of data concealment science that aiming to be reached a coveted security scale in the interchange of private not clear commercial and military data. This research offers a novel technique for steganography based on hiding data inside the clusters that resulted from fuzzy clustering. T

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Publication Date
Wed Nov 01 2023
Journal Name
Journal Of Dentistry
The in-vitro development of novel enzyme-based chemo-mechanical caries removal agents
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Objectives: Bromelain is a potent proteolytic enzyme that has a unique functionality makes it valuable for various therapeutic purposes. This study aimed to develop three novel formulations based on bromelain to be used as chemomechanical caries removal agents. Methods: The novel agents were prepared using different concentrations of bromelain (10–40 wt. %), with and without 0.1–0.3 wt. % chloramine T or 0.5–1.5 wt. % chlorhexidine (CHX). Based on the enzymatic activity test, three formulations were selected; 30 % bromelain (F1), 30 % bromelain-0.1 % chloramine (F2) and 30 % bromelain-1.5 % CHX (F3). The assessments included molecular docking, Fourier-transform infrared spectroscopy (FTIR), viscosity and pH measurements. The efficie

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Publication Date
Wed Nov 01 2023
Journal Name
Journal Of Dentistry
The in-vitro development of novel enzyme-based chemo-mechanical caries removal agents
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Objectives Bromelain is a potent proteolytic enzyme that has a unique functionality makes it valuable for various therapeutic purposes. This study aimed to develop three novel formulations based on bromelain to be used as chemomechanical caries removal agents. Methods The novel agents were prepared using different concentrations of bromelain (10–40 wt. %), with and without 0.1–0.3 wt. % chloramine T or 0.5–1.5 wt. % chlorhexidine (CHX). Based on the enzymatic activity test, three formulations were selected; 30 % bromelain (F1), 30 % bromelain-0.1 % chloramine (F2) and 30 % bromelain-1.5 % CHX (F3). The assessments included molecular docking, Fourier-transform infrared spectroscopy (FTIR), viscosity and pH measurements. The efficiency

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Sun Jun 30 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The impact of strategic planning for electronic services to developing cash bank deposits: An Applied research for a sample of Iraqi private banks
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               The bank deposits is fuel banking activity and raw material products for the commercial bank and the basis of its activity and its lifetime So the bank, which seeks to continue the successful development of the volume of cash deposits has translated the work of the bank to meet the needs of different sectors by providing the necessary funding, and from this point of view was the research problem a lack of interest departments of banking services to commercial banks as a means for the development of electronic cash deposits have, and which represents the basis for the supplier commercial bank fund.

 

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Publication Date
Wed Apr 01 2009
Journal Name
International Journal Of Applied Environmental Sciences
An expert System for Predicting the Effects of Noise Pollution on Grass Trimming Task Using Fuzzy Modeling
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Grass trimming operation is widely done in Malaysia for the purpose of maintaining highways. Large number of operators engaged in this work encounters high level of noise generated by back pack type grass trimmer used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known. For predicting the work efficiency deterioration, fuzzy tool has been used in present research. It has been established that a fuzzy computing system will help in identification and analysis of fuzzy models fuzzy system offers a convenient way of representing the relationships between the inputs and outputs of a system in the form of IF-THEN rules. The paper presents

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

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