Background: The aim of this study was to evaluate the effect of three types of light curing devices QTH, LED and Flashmax on the surface microhardness of three types of bulkfill composite resins; Filtek Bulkfill posterior composite ( 3M), Tetric Evo Ceram ( Ivoclar Vivadent) and Sonicfill composite ( Kerr) Materials and methods: Total number of 90 samples was prepared, 30 samples for each type of bulkfill composite, were divided into three main groups, group A: Filtek posterior bulkfil (3M), group B: Tetric Evo Ceram (Ivoclar Vivadent) and group C: contain Sonicfill composite (kerr). Which then divided into three subgroups (n= 10) (1) Samples cured by QTH system (2) Samples cured by LED system and (3) samples cured by Flashmax system the

In Iraq, more than 1031 school projects have been halted due to disputes and claims resulting from financial, contractual, or other issues. This research aims to identify, prioritize, and allocate the most critical risk factors that threaten these projects’ success for the duration (2017-2022). Based on a multi-step methodology developed through systematic literature reviews, realistic case studies, and semi-structured interviews, 47 risk factors were identified. Based on 153 verified responses, the survey reveals that the top-ranked risk factors are corruption and bribery, delaying the payments of the financial dues to the contractors or sub-contractors, absence of risk management strategy, multiple change orders due

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through tha

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

This paper presents the design, construction and investigates an experimental study of a parabolic Trough Solar Collector (PTSC). It is constructed of multi – piece glass mirror to form the parabolic reflector (1.8 m ? 2.8 m) its form were checked with help of a laser and carbon steel rectangular as receiver. Sun tracker has been developed (using two – axis) to track solar PTSC according to the direction of beam propagation of solar radiation. Using synthetic oil as a heat transfer its capability to heat transfer and load high temperature (?400 oc). The storage tank is fabricated with stainless steel of size 50 L. The experimental tests have been carried out in Baghdad climatic conditions (33.3o N, 44.4o E) during selective days of the