In this work, an efficient energy management (EEM) approach is proposed to merge IoT technology to enhance electric smart meters by working together to satisfy the best result of the electricity customer's consumption. This proposed system is called an integrated Internet of things for electrical smart meter (2IOT-ESM) architecture. The electric smart meter (ESM) is the first and most important technique used to measure the active power, current, and energy consumption for the house’s loads. At the same time, the effectiveness of this work includes equipping ESM with an additional storage capacity that ensures that the measurements are not lost in the event of a failure or sudden outage in WiFi network. Then then these measurement

The [2-aminobenzothiazole]was reacted with [2,4,6 triyhydroxy-acetophenon monohydrate] to give a new ligand [2-N-2,4,6-trihydroxyacetophenonyliden benzothiazole] [H3L]. This ligand was reacted with metal ions ( CoII, NiII,CuII and ZnII) in methanol as solvent with ( 1:2 ) metal : ligand ratio to give a series of new complexes with general formula [ M(H2L)2],(where:M= CoII, NiII ,CuIIand, ZnII).All compounds were characterized by spectroscopic methods ( I.R , U.V – vis,HPLC) atomic absorption, along with chloride content and conductivity measurements. According to the data of these measurements we suggested a tetrahedral

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distrib

The aim of this research is to benefit from recycl the aircraft waste oils which is discarded in sewage network, to be used in preparation of greases for industrial purposes and to reduce the environmental pollution. In this research synthetic greases were prepared with special specifications by mixing the waste oils after treating with (silica gel as adsorbent agent, and filtration to precipitate impurities then heated to 110 C? to get rid of water) bentonite produced in Iraq which is available and cheap with existence of high density polyethylene at specific conditions of ( heating and mixing) . The best weight proportion were reached, then paraffin wax and additives were added to improve the properties of grease and give the

Abstract: In this research, nanofibers have been prepared by using an electrospinning method. Three types of polymer (PVA, VC, PMMA) have been used with different concentration. The applied voltage and the gap length were changed. It was observed that VC is the best polymer than the other types of polymers.

In this research, nanofibers have been prepared by using an electrospinning method. Three types of polymer (PVA, VC, PMMA) have been used with different concentration. The applied voltage and the gap length were changed. It was observed that VC is the best polymer than the other types of polymers.

Polyvinyl alcohol, (PVA) was prepared using polyvinyl acetate emulsion (manufactured by Al-Jihad factory,
That-Al-Sawary Company) as a local raw material. In this investigation, polyvinyl acetate emulsion was converted to
solid form by coagulation the polymer from its emulsion using sodium sulphate salt as coagulant aid, then alcoholyzed
the solid polyvinyl acetate in methanol using sodium hydroxide as catalyst, polyvinyl alcohol produced by this method is
a dry, white to yellow powder.
Three affecting variables on the degree of hydrolysis of PVA were studied, these variable are Catalyst to
polymer weight ratio in the range of 0.01 – 0.06, reaction time in the range of 20 – 90 min, and reaction temperature in
the