Abstract In this study, an investigation is conducted to realise the possibility of organic materials use in radio frequency (RF) electronics for RF-energy harvesting. Iraqi palm tree remnants mixed with nickel oxide nanoparticles hosted in polyethylene, INP substrates, is proposed for this study. Moreover, a metamaterial (MTM) antenna is printed on the created INP substrate of 0.8 mm thickness using silver nanoparticles conductive ink. The fabricated antenna performances are instigated numerically than validated experimentally in terms of S11 spectra and radiation patterns. It is found that the proposed antenna shows an ultra-wide band matching bandwidth to cover the frequencies from 2.4 to 10 GHz with bore-sight gain variation from 2.2 to 3.43 dBi at maximum. The antenna size is compacted to a 32 mm × 24 mm using a fractal-shaped MTM when mounted on the INP substrate with a relative permittivity ɛr = 3.106−j0.0314 and a relative permeability µr = 1.548−j0.0907. Finally, the maximum obtained voltage from the proposed antenna is found about 2 V at 2.45 GHz and 2.5 V at 5.8 GHz, where, the corresponding measured equivalent isotropic radiated power is about 2.35 W at 2.45 GHz and 6.12 W at 5.8 GHz.
Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s
... Show MoreThis work is concerned with a two stages four beds adsorption chiller utilizing activated carbon-methanol adsorption pair that operates on six separated processes. The four beds that act as thermal compressors are powered by a low grade thermal energy in the form of hot water at a temperature range of 65 to 83 °C. As well as, the water pumps and control cycle consume insignificant electrical power. This adsorption chiller consists of three water cycles. The first water cycle is the driven hot water cycle. The second cycle is the cold water cycle to cool the carbon, which adsorbs the methanol. Finally, the chilled water cycle that is used to overcome the building load. The theoretical results showed that average cycle cooling power
... Show MoreInformation processing has an important application which is speech recognition. In this paper, a two hybrid techniques have been presented. The first one is a 3-level hybrid of Stationary Wavelet Transform (S) and Discrete Wavelet Transform (W) and the second one is a 3-level hybrid of Discrete Wavelet Transform (W) and Multi-wavelet Transforms (M). To choose the best 3-level hybrid in each technique, a comparison according to five factors has been implemented and the best results are WWS, WWW, and MWM. Speech recognition is performed on WWS, WWW, and MWM using Euclidean distance (Ecl) and Dynamic Time Warping (DTW). The match performance is (98%) using DTW in MWM, while in the WWS and WWW are (74%) and (78%) respectively, but when using (
... Show MoreSocio-scientific issues provide a great platform to both engage students in scientific topics and assess their understanding of scientific concepts. Nancy R. Singer, Amy Lannin, Maha Kareem, William Romine, and Katie Kline report on the STEM Literacy Project, a three-year National Science Foundation grant that aimed to improve STEM teachers’ knowledge and integration of literacy in their classrooms. They describe teachers’ professional learning, scenario-based assessments and other strategies they incorporated in their STEM classrooms, and how writing enables students to understand real-world issues.
The design and implementation of an active router architecture that enables flexible network programmability based on so-called "user components" will be presents. This active router is designed to provide maximum flexibility for the development of future network functionality and services. The designed router concentrated mainly on the use of Windows Operating System, enhancing the Active Network Encapsulating Protocol (ANEP). Enhancing ANEP gains a service composition scheme which enables flexible programmability through integration of user components into the router's data path. Also an extended program that creates and then injects data packets into the network stack of the testing machine will be proposed, we will call this program
... Show MorePolyaniline Multi wall Carbon nanotube (PANI/MWCNTs) nanocomposite thin films have been prepared by Plasma jet polymerization at low frequency on glass substrate with preliminary deposited aluminum electrodes to form Al/PANI-MWCNT/Al surface-type capacitive humidity sensors, the gap between the electrodes about 50 μm and the MWCNTs weight concentration varied between 0, 1, 2, 3, 4%. The diameter of the MWCNTs was in the range of 8-15 nm and the length 10-55 μm. The capacitance-humidity relationships of the sensors were investigated at humidity levels from 35 to 90% RH. The electrical properties showed that the capacity increased with increasing relative humidity, and that the sensitivity of the sensor increases with the increase of the
... Show MoreRecommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o
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