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 satisfied. It divides the measured data for actual power (A_p ) of the electrical model into two portions: the training portion is selected for different maximum actual powers, and the validation portion is determined based on the minimum output power consumption and then used for comparison with the actual required input power. Simulation results show the energy expenditure problem can be solved with good accuracy in energy consumption by reducing the maximum rate (A_p ) in a given time (24) hours for a single house, as well as electricity’s bill cost, is reduced.
One of these plants utilized in traditional medicine is Lactuca seriolla Linn., which belongs to the Asteraceae family. It goes by a variety of common names in the world, including prickly lettuce, wild lettuce, jagged lettuce, and Kahu and khas. The work aimed to isolate and characterize some bioactive constituent(s) from the aerial part of Lactuca serriola utilizing Combiflash NEXTGEN and high-performance liquid chromatography (HPLC). Lactuca serriola (aerial part) was extracted with 80% ethanol, then fractionated with hexane. Then 250 mg of hexane extract was mixed with 4 g of silica gel and loaded in cartilage, then bounded to the gold column of combi flash using a solvent system comprised of ethyl acetat
... Show MoreThe prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traff
... Show MoreThe research aims to reveal the impact of media policy in Iraqi media outlets on the level of objectivity in these outlets. A study from the communicators’ point of view where the researcher used a survey method on the communicators in media outlets to reveal the extent of media policies knowledge as well as the pressures exerted by this policy on communicators in media outlets. It also reveals the extent of their commitment to objectivity, neutrality in dealing with information and the way used to transfer it.
The research sample included (179) respondents from communicators in a range of Media outlets such as (Press, Radio, and Television), The researcher was careful with the diversity of the sample, and
Thin films of Zinc Selenide ZnSe have been prepared by using thermal evaporation in vacuum technique (10-5Torr) with thickness (1000, 2700, 4000) A0 and change electrode material and deposited on glass substrates with temperature (373K) and study some electrical properties at this temperature . The graphs shows linear relation between current and voltage and the results have shown increases in the value of current and electrical conductivity with increase thickness and change electrode material from Aluminum to Copper
This investigation reports application of a mesoporous nanomaterial based on dicationic ionic liquid bonded to amorphous silica, namely nano-N,N,N′,N′-tetramethyl-N-(silican-propyl)-N′-sulfo-ethane-1,2-diaminium chloride (nano-[TSPSED][Cl]2), as an extremely effectual and recoverable catalyst for the generation of bis(pyrazolyl)methanes and pyrazolopyranopyrimidines in solvent-free conditions. In both synthetic protocols, the performance of this catalyst was very useful and general and presented attractive features including short reaction times with high yields, reasonable turnover frequency and turnover number values, easy workup, high performance under mild conditions, recoverability and reusability in 5 consecutive runs without lo
... Show MoreIn this study, biodiesel was prepared from chicken fat via a transesterification reaction using Mussel shells as a catalyst. Pretreatment of chicken fat was carried out using non‐catalytic esterification to reduce the free fatty acid content from 36.28 to 0.96 mg KOH/g oil using an ethanol/ fat mole ratio equal to 115:1. In the transesterification reaction, the studied variables were methanol: oil mole ratio in the range of (6:1 ‐ 30:1), catalyst loading in the range of (9‐15) wt%, reaction temperature (55‐75 °C), and reaction time (1‐7) h. The heterogeneous alkaline catalyst was greenly synthesized from waste mussel shells throughout a calcin
In this study, biodiesel was prepared from chicken fat via a transesterification reaction using Mussel shells as a catalyst. Pretreatment of chicken fat was carried out using non‐catalytic esterification to reduce the free fatty acid content from 36.28 to 0.96 mg KOH/g oil using an ethanol/ fat mole ratio equal to 115:1. In the transesterification reaction, the studied variables were methanol: oil mole ratio in the range of (6:1 ‐ 30:1), catalyst loading in the range of (9‐15) wt%, reaction temperature (55‐75 °C), and reaction time (1‐7) h. The heterogeneous alkaline catalyst was greenly synthesized from waste mussel shells throughout a calcin