The university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a higher-level method that selects low-level heuristics (LLH) sequence which further generates an optimal solution. The proposed a

This work examines numerically the effects of particle size, particle thermal conductivity and inlet velocity of forced convection heat transfer in uniformly heated packed duct. Four packing material (Aluminum, Alumina, Glass and Nylon) with range of thermal conductivity (from200 W/m.K for Aluminum to 0.23 W/m.K for Nylon), four particle diameters (1, 3, 5 and 7 cm), inlet velocity ( 0.07, 0.19 and 0.32 m/s) and constant heat flux ( 1000, 2000 and 3000 W/ m ²) were investigated. Results showed that heat transfer (average Nusselt number Nu_av) increased with increasing packing conductivity; inlet velocity and heat flux, but decreased with increasing particle size.Also, Aluminum average Nusselt number is about (0.85,2.

Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul

A simple , sensitive and accurate spectrophotometric method for the trace determination of bismuth (III) has been developed .This method is based on the reaction of bismuth (III) with arsenazo(III) in acid solution (pH=1.9) to form a blue water soluble complex which exhibits maximum absorption at 612nm .Beer's law is obeyed over the concentration range of 2-85 ?g bismuth (III) in a final volume of 20 mL( i.e. 0.1 – 4.25?g.mL-1) with a correlation coefficient of (0.9981) and molar absorptivity 1.9×104 L.mol-1.cm-1 . The limit of detection (LOD) and the limit of quantification (LOQ) are 0.0633 and 0.0847 ?g.mL-1 , respectively . Under optimum conditions,the stoichiometry of the reaction between bismuth (III) and arsenazo(III) r

The study was conducted in the poultry field, College of Agriculture, Al-Muthanna University from 1/3/2018 to 6/4/2018 to determine the effect of commercial Ascomax powder produced from seaweed (Ascophyllum nodocum) on some productive performance of broilers. A total of 400, one day, Ross 308 broiler chicks were used for 35 days. The chicks were randomly distributed to 4 treatments, four replicates per treatment (25 chick / replicate). The treatments were as follows: T1: (control treatment), while T2, T3 and T4 added diet by Ascomax powder by 1, 1.5 and 2 g per 1 kg of the basal diet, respectively. The results of the study showed a significant superiority (P <0.05) for the added Ascomax powder treatments compared to the treatment of control

This paper deals with the preparation and investigation studies of a number of new complexes of Cu(II) , Zn(II) , Hg(II) , Ag(I) , Pt(IV) and Pb(II).The complexes were formed by the reaction of the mentioned metal ions with the ligand which is derived from oxadiazole (OXB), 2- (2-butyl) thio-5- phenyl – 1,3,4 – oxadiazole in the mole ratio (1:1) , (1:2) and (1:3) (metal to ligand ).The result complexes having general formulae :M(OXB)Cl2] [M(OXB)X2]H2O [ M= Cu(II) , Zn(II) M= Hg(II) , Pb(II) [M(OXB)2 X2] X= Cl– M = Cu (II), Zn (II), Hg (II), Pb (II) X= Cl–, NO3-, CH3COO- [Pt(OXB)3]Cl4 [Ag(OXB)]NO32-(2-??????? ) ???? -5- ???

Diverting river flow during construction of a main dam involves the construction of cofferdams, and tunnels, channels or other temporary passages. Diversion channels are commonly used in wide valleys where the high flow makes tunnels or culverts uneconomic. The diversion works must form part of the overall project design since it will have a major impact on its cost, as well as on the design, construction program and overall cost of the permanent works. Construction costs contain of excavation, lining of the channel, and construction of upstream and downstream cofferdams. The optimization model was applied to obtain optimalchannel cross section, height of upstream cofferdam, and height of downstream cofferdamwith minimum construction cost