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Investigation of Energy Efficient Clustering Algorithms in WSNs: A Review
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In recent years, Wireless Sensor Networks (WSNs) are attracting more attention in many fields as they are extensively used in a wide range of applications, such as environment monitoring, the Internet of Things, industrial operation control, electric distribution, and the oil industry. One of the major concerns in these networks is the limited energy sources. Clustering and routing algorithms represent one of the critical issues that directly contribute to power consumption in WSNs. Therefore, optimization techniques and routing protocols for such networks have to be studied and developed. This paper focuses on the most recent studies and algorithms that handle energy-efficiency clustering and routing in WSNs. In addition, the prime issues in these networks are discussed and summarized using comparison tables, including the main features, limitations, and the kind of simulation toolbox. Energy efficiency is compared between some techniques and showed that according to clustering mode “Distributed” and CH distribution “Uniform”, HEED and EECS are best, while in the non-uniform clustering, both DDAR and THC are efficient. According to clustering mode “Centralized” and CH distribution “Uniform”, the LEACH-C protocol is more effective.

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Publication Date
Fri Jan 01 2021
Journal Name
Artificial Intelligence For Covid-19
An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings
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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Engineering
Energy and Exergy Analyses of Heat Pump Cycle with Refrigerant Injection Technology
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The effect of refrigerant injection techniques on the performance of heat pump system based on exergy analysis was studied theoretically. Three refrigerant injection techniques were used; the first was achieved by injected vapour in volume ratios from 1 to 7% in the accumulator. The second was injection liquid refrigerant in the discharge line with the aid of Liquid Pressure Amplification (LPA) pump, with volume ratios from 1 to 10%. The third was a hybrid injection with volume ratios of injected vapour and liquid varied from 1 to 3% and 1 to 10%; respectively. The following improvements in cycle performance were observed. For vapour injection technique, the best ratio of injection was 5%, the exergy destruction reduced

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Publication Date
Wed Mar 16 2022
Journal Name
2022 Muthanna International Conference On Engineering Science And Technology (micest)
Virtual Performance Evaluation of Net-Zero Energy Building (NZEB) Using BIM Analysis
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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Information Technology Management
The impact of social commerce determinants on social capital for energy sectors
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This study investigates the constructs and related theories that drive social capital in energy sector from the intention perspectives. This research uses theories of 'social support' and 'planned behaviour' alongside satisfaction and perceived value to propose a research model that drives social capital for energy sectors in Malaysia. The model reveals that the Theories of Planned Behaviour (TPB) and Social Support Theory (SST) alongside satisfaction and perceived value factors promote social capital development in energy sectors. Using PLS-SEM to analyse data gathered from energy sector employees in Malaysia, this research demonstrates that social capital is present when there is trust and loyalty among the users and positively effects en

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Engineering
Using Nanoparticles for Enhance Thermal Conductivity of Latent Heat Thermal Energy Storage
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Phase change materials (PCMs) such as paraffin wax can be used to store or release large amount of energy at certain temperature at which their solid-liquid phase changes occurs. Paraffin wax that used in latent heat thermal energy storage (LHTES) has low thermal conductivity. In this study, the thermal conductivity of paraffin wax has been enhanced by adding different mass concentration (1wt.%, 3wt.%, 5wt.%) of (TiO2) nano-particles with about (10nm) diameter. It is found that the phase change temperature varies with adding (TiO2) nanoparticles in to the paraffin wax. The thermal conductivity of the composites is found to decrease with increasing temperature. The increase in thermal conductivity ha

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Determination of Welding Velocity and Arc Energy for Fusion MAG Welding Joint
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 Abstract

This paper is an experimental work to determinate the effect of welding velocity and formed arc energy for CO2-MAG fusion weld pool. The input parameters (arc voltage, wire feed speed and gas flow rate) were investigated to find their effects on the weld joint efficiency. Design of experiment with response surface methodology technique was used to build empirical mathematical models for welding velocity and arc energy in term of the input welding parameters. The predicted quadratic models were statistically checked for adequacy purpose by ANOVA analysis. Additionally, numerical optimization was conducted to obtain the optimum values for welding velocity and arc energy. A good agree

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Publication Date
Mon Mar 01 2021
Journal Name
Key Engineering Materials
Experimental Investigation of Reinforced Concrete Columns with Steel Embedded Tubes
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This study aimed to investigate the influence of longitudinal steel embedded tubes located at the center of the column cross-section on the behavior of reinforced concrete (RC) columns. The experimental program consisted of 8 testing pin-ended square sectional columns of 150×150 mm, having a total height of 1400 mm, subjected to eccentric load. The considered variables were the steel square tube sizes of 25, 51 and 68 mm side dimensions and the load eccentricity (50 and 150) mm. RC columns were concealed steel tubes with hollow ratios of 3%, 12% and 20% depending on tube sizes used. The experimental results indicated an improvement in the overall behavior of eccentric columns when steel embedded tubes are used. The maximum gain in

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Publication Date
Sat Nov 01 2014
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Theoretical Investigation of Impact Dynamic Plasticity for CK45
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Abstract

This paper represents a study of the effect of the soil type, the drilling parameters and the drilling tool properties on the dynamic vibrational behavior of the drilling rig and its assessment in the drilling system. So first, an experimental drilling rig was designed and constructed to embrace the numerical work.

The experimental work included implementation of the drill-string in different types of soil with different properties according to the difference in the grains size, at different rotational speeds (RPM), and different weights on bit (WOB) (Thrust force), in a way that allows establishing the charts that correlate the vibration acceleration, the rate of penetration (ROP), and the power

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Publication Date
Fri May 03 2019
Journal Name
Photonics
Design Investigation of 4 × 4 Nonblocking Hybrid Plasmonic Electrooptic Switch
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This paper proposes a compact, plasmonic-based 4 × 4 nonblocking switch for optical networks. This device uses six 2 × 2 plasmonic Mach-Zehnder switch (MZS), whose arm waveguide is supported by a JRD1 polymer layer as a high electro-optic coefficient material. The 4 × 4 switch is designed in COMSOL environment for 1550 nm wavelength operation. The performance of the proposed switch outperforms those of conventional (nonplasmonic) counterparts. The designed switch yields a compact structure ( 500 × 70   µ m 2 ) having V π L = 12   V · µ m , 1.5 THz optical bandwidth, 7.7 dB insertion loss, and −26.5 dB crosstalk. The capability of the switch to route 8 × 40 Gbps WDM signal is demonstrated successfully.

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