The health of Roadway pavement surface is considered as one of the major issues for safe driving. Pavement surface condition is usually referred to micro and macro textures which enhances the friction between the pavement surface and vehicular tires, while it provides a proper drainage for heavy rainfall water. Measurement of the surface texture is not yet standardized, and many different techniques are implemented by various road agencies around the world based on the availability of equipment’s, skilled technicians’ and funds. An attempt has been made in this investigation to model the surface macro texture measured from sand patch method (SPM), and the surface micro texture measured from out flow time (OFT) and British pendulum number (BPN) testing techniques. Flexible and rigid pavement surfaces have been investigated in this work. A total of 300 testing locations have been selected, and the three testing procedures were conducted for each location. The modeling was conducted by implementation of the statistical package (SPSS-19) and the artificial neural network package (ANN). Data were fed to the packages and the correlation of each testing method with the other two methods have been obtained through statistical analysis. It was concluded that (ANN) software is more reliable in providing the correlation between the testing techniques implemented as compared to (SPSS-19) software. Modeling could provide an instant determination of pavement surface health when the advanced testing techniques are scares.
Today we are witnessing huge scientific and technical progress so we need more skills and methods of thinking that needs to be acquired by the teacher, as the importance of computers in education there are many teachers suffering of the difficulty in teaching for pupils . researchers tried to find a good suitable way with the technological interests for now which represent by computer design software and the introduction of enrichment activities in the curriculum because it is one of a contemporary trends for the development of the Arabic language with various levels of education and knowing if this program has negative or positive impact.
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... Show MoreThe need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat
... Show MoreThe objective of the present paper is to examine the effect of Recycled Asphalt Pavement (RAP) on marshall properties and indirect tensile strength of HMA through experimental investigation. A mixture with 0% RAP was used as a control mix to evaluate the properties of mixes with 5%, 10%, and 15% RAP. One type of RAP was brought from Bab Al-moadam’s road in Baghdad for this purpose. The experimental testing program included Marshall and Indirect Tensile Strength tests. The results indicated that the bulk density, flow and VFA increase with the increasing of the percentage of RAP, while increasing in RAP results decreases in VTM and VMA values. Furthermore, the stability is changed from 10.1 kN for the control mix to12, 13.6 and 11.7 kN
... Show MoreThe majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value <0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe
To damp the low-frequency oscillations which occurred due to the disturbances in the electrical power system, the generators are equipped with Power System Stabilizer (PSS) that provide supplementary feedback stabilizing signals. The low-frequency oscillations in power system are classified as local mode oscillations, intra-area mode oscillation, and interarea mode oscillations. Double input multiband Power system stabilizers (PSSs) were used to damp out low-frequency oscillations in power system. Among dual-input PSSs, PSS4B offers superior transient performance. Power system simulator for engineering (PSS/E) software was adopted to test and evaluate the dynamic performance of PSS4B model on Iraqi national grid. The results showed
... Show MoreTo damp the low-frequency oscillations which occurred due to the disturbances in the electrical power system, the generators are equipped with Power System Stabilizer (PSS) that provide supplementary feedback stabilizing signals. The low-frequency oscillations in power system are classified as local mode oscillations, intra-area mode oscillation, and interarea mode oscillations. Double input multiband Power system stabilizers (PSSs) were used to damp out low-frequency oscillations in power system. Among dual-input PSSs, PSS4B offers superior transient performance. Power system simulator for engineering (PSS/E) software was adopted to test and evaluate the dynamic performance of PSS4B model on Iraqi national grid. The res
... Show MoreCOVID-19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduce
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
... Show MoreBearing capacity of soil is an important factor in designing shallow foundations. It is directly related to foundation dimensions and consequently its performance. The calculations for obtaining the bearing capacity of a soil needs many varying parameters, for example soil type, depth of foundation, unit weight of soil, etc. which makes these calculation very variable–parameter dependent. This paper presents the results of comparison between the theoretical equation stated by Terzaghi and the Artificial Neural Networks (ANN) technique to estimate the ultimate bearing capacity of the strip shallow footing on sandy soils. The results show a very good agreement between the theoretical solution and the ANN technique. Results revealed that us
... Show MoreWaste materials might be utilized in various applications, such as sustainable roller compacted concrete pavements (RCCP), to lessen the negative environmental consequences of construction waste. The impacts of utilizing (brick, thermostone, granite, and ceramic) powders on the mechanical characteristics of RCCP are investigated in this study. To achieve this, the waste materials were crushed, grounded, and blended before being utilized as filler in the RCCP. After the mixes were prepared, compressive strength, splitting tensile strength, flexural strength, water absorption, density, and porosity were all determined. According to the research results, adding some of these powders, mainly brick and granite powder, enhances the mechanical
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