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.
Fluidization process is widely used by a great assortment of industries worldwide and represents a trillion dollar industry [6]. They are currently used in separation, classification, drying and mixing of particles, chemical reactions and regeneration processes; one of these processes is the mass transfer from an immersed surface to a gas fluidized bed
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The present paper deals with experimental investigation of the performance of air cooled split air conditioner, with evaporative water mist pre cooling to increase the cooling capacity and reduce the consumption power under hot and dry climate. This investigation considers how the performance can be enhanced by using water mist to pre-cool ambient air entering the condensers by adiabatic cooling process which depends on the ambient air wet bulb temperature; as well the condensing temperature and condensing pressure will be decreased accordingly. So the cooling capacity would be increased and consumption power would be decreased, consequently the energy ratio, EER would be improved. The performance of air cooled air conditioner with water
... Show MoreIn this paper, a FPGA model of intelligent traffic light system with power saving was built. The intelligent traffic light system consists of sensors placed on the side's ends of the intersection to sense the presence or absence of vehicles. This system reduces the waiting time when the traffic light is red, through the transition from traffic light state to the other state, when the first state spends a lot of time, because there are no more vehicles. The proposed system is built using VHDL, simulated using Xilinx ISE 9.2i package, and implemented using Spartan-3A XC3S700A FPGA kit. Implementation and Simulation behavioral model results show that the proposed intelligent traffic light system model satisfies the specified operational req
... Show MoreThe cytotoxicity of different concentrations of purified methionine γ- lyase from Pseudomonas putida on cancer cell lines (RD, AMN3 and AMGM) at 96 hr was studied. The bacterial enzyme with concentration 1000µg/ml was revealed highly cytotoxicity against cancer cell lines in comparison with other concentrations whereas slight cytotoxicity was observed on normal cell (REF).
In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf
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