The research aims to investigate the existence of a direct causal relationship between selected agricultural variables: agricultural output (as a representative of growth in the agricultural sector), agricultural terms of trade as a completely new variable in agricultural studies in recent years, agricultural labour which is an important part in the total workforce for Iraq, and finally, agricultural investment because of its importance and vital role in the production process, creating job opportunities, and then raising the level of employment, then it's role to achieving agricultural growth and development. For this purpose, the researchers used the Toda-Yamamoto causality methodology for a time series covering from 1990 to 2019. The research found a causal relationship between the agricultural terms of trade TOT and the agricultural labour LA towards agricultural product AP, and the existence of a significant causal relationship from all variables towards agricultural investment INV. Therefore, the research recommends taking in consideration the results mentioned above and working to exploit the opportunities provided by the relationships among studied variables to avoid the reasons for problems such as the presence of terms of trade not in the interest of Iraq, as well as emphasizing the good opportunities, such as the crucial role of agricultural investment in raising the level of agricultural product and employment. As well as the need to adopt the terms of trade criteria as one of the important indicators in making government policies related to the production and export of agricultural products.
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur
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Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
Simulation of the Linguistic Fuzzy Trust Model (LFTM) over oscillating Wireless Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Network
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Scheduling considered being one of the most fundamental and essential bases of the project management. Several methods are used for project scheduling such as CPM, PERT and GERT. Since too many uncertainties are involved in methods for estimating the duration and cost of activities, these methods lack the capability of modeling practical projects. Although schedules can be developed for construction projects at early stage, there is always a possibility for unexpected material or technical shortages during construction stage. The objective of this research is to build a fuzzy mathematical model including time cost tradeoff and resource constraints analysis to be applied concurrently. The proposed model has been formulated using fuzzy the
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The surplus glycerol produced from biodiesel production process as a by-product with high quantity can be considered as a good source to prepare glycerol carbonate (GC) whereas with each 1000 kg from biodiesel obtains 100 kg from glycerol. Glycerol converted to glycerol carbonate over bio-char as a catalyst prepared by slow pyrolysis process under various temperatures from 400 ᴼC to 800 ᴼC. The char prepared at 700 ᴼC considered as a best one between the others which was manufactured to activate the transesterification reaction. GC have large scale of uses such as liquid membrane in gas separation, surfactants ,detergents , blowing agent , in plastics industry, in Pharmaceutical industry and electrolytes in lithium batteries.
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The aim of our study is to reveal the effect of steel reinforcement details,tensile steel reinforcement ratio, compressed reinforcing steel ratio,reinforcing steel size, corner joint shape on the strength of reinforcedconcrete Fc' and delve into it for the most accurate details and concreteconnections about the behavior and resistance of the corner joint ofreinforced concrete, Depending on the available studies and sources inaddition to our study, we concluded that each of these effects had a clearrole in the behavior and resistance of the corner joint of reinforced concreteunder the influence of the negative moment and yield stress. A studyof the types of faults that can be reinforced angle joints obtains detailsand conditions of c
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Extraction of copper (Cu) from aqueous solution utilizing Liquid Membrane technology (LM) is more effective than precipitation method that forms sludge and must be disposed of in landfills. In this work, we have formulated a liquid surfactant membrane (LSM) that uses kerosene oil as the main diluent of LSM to remove copper ions from the aqueous waste solution through di- (2-ethylhexyl) phosphoric acid - D2EHPA- as a carrier. This technique displays several advantages including one-stage extraction and stripping process, simple operation, low energy requirement, and. In this study, the LSM process was used to transport Cu (II) ions from the feed phase to the stripping phase, which was prepared, using H2SO4. For LSM p
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