Effective decision-making process is the basis for successfully solving any engineering problem. Many decisions taken in the construction projects differ in their nature due to the complex nature of the construction projects. One of the most crucial decisions that might result in numerous issues over the course of a construction project is the selection of the contractor. This study aims to use the ordinal priority approach (OPA) for the contractor selection process in the construction industry. The proposed model involves two computer programs; the first of these will be used to evaluate the decision-makers/experts in the construction projects, while the second will be used to formulate the OPA mathematical model. The experts’ interview was used to identify the criteria of evaluation process of the decision-makers/experts, while Delphi survey with principal component analysis (PCA) was conducted to identify the required selection criteria of the construction projects contractors. The results illustrate that there are 20 criteria for selecting the construction contractor, and 7 criteria for evaluating the decision-makers/experts in the construction projects. Finally, the proposed model has been applied in a real construction project, and showed good results.
A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.
The removal of commercial orange G dye from its aqueous solution by adsorption on tobacco leaves (TL) was studied in respect to different factor that affected the adsorption process. These factors including the tobacco leaves does, period of orange G adsorption, pH, and initial orange G dye concentration .Different types of isotherm models were used to describe the orange G dye adsorption onto the tobacco leaves. The experimental results were compared using Langmuir, and frundlich adsorption isotherm, the constants for these two isotherm models was determined. The results fitted frundlich model with value of correlation coefficient equal to (0.981). The capacity of adsorption for the orange G dye was carried out using various kinetic models
... Show MoreThis research deals with the most important heritage in Iraq, which are the Iraqi marshes, especially Abu Zarag marsh in Al-Nasiriyah city south of Iraq. The research is divided into two parts. The first part deals with evaluating the water quality parameters of Abu Zarag marsh for the period from December 2018 to April 2019 which is the flooding season. The parameters are Temperature, pH, Electrical Conductivity, Total Dissolved Solids, Alkalinity, Total Hardness, Turbidity, Dissolved Oxygen, Sulfate, Nitrate. The second part is a comparison between the water quality parameters during the recent period with the same period during the previous years from 2014 to 2019. The results are
The phenomena of Dust storm take place in barren and dry regions all over the world. It may cause by intense ground winds which excite the dust and sand from soft, arid land surfaces resulting it to rise up in the air. These phenomena may cause harmful influences upon health, climate, infrastructure, and transportation. GIS and remote sensing have played a key role in studying dust detection. This study was conducted in Iraq with the objective of validating dust detection. These techniques have been used to derive dust indices using Normalized Difference Dust Index (NDDI) and Middle East Dust Index (MEDI), which are based on images from MODIS and in-situ observation based on hourly wi
The research aimed at designing teaching sessions using the self-scheduling strategy with a competitive style in learning handball as well as identifying differences between pre and post tests in both groups in learning short and long passes in handball. The researchers used the experimental method on 2nd-grade secondary school students. The researchers concluded using the self-scheduling strategy due to its positive effect on learning short and long handball passes in handball. Finally, the researchers recommended applying strategies and styles in teaching different school levels as well as making similar studies using teaching strategies and styles for learning handball skills in students.
In this study, the fission track registration technique with the CR-39 detector are using to determination the uranium concentrations for seventeen samples of teeth distributed in four districts in Baghdad City .Five samples taken from both Al-Durra District and Al-Jadiriyia District, Four samples taken from Al-Karrda (Alaatar street) Taken four samples and three samples taken from Al-Zuafrania and by 0.5gm in weight and 1.5 mm in thickness. The uranium concentrations in teeth samples measured by using fission tracks registration in (CR-39) track detector that caused by the bombardment of (U) with thermal neutrons from (241 Am-Be) neutron source that has flux of (5 ×103 n cm-2 s-1). The concen
... Show MoreIn light of the increasing interest in Child-rearing in nurseries and kindergartens and the most important experiences gained by the child at this stage that form the basis for the subsequent stages of her/his physical mental and social growth.
The significance of the research concentrates the need to asses the affecting variables on the child growth to create opportunities for her/him to have intact rearing.
The research also aims to classify these variables at each age level and highlight its moral role.
The problem of the research is the lack of clarity of different variables impact of the child growth in different age levels in nurseries and kindergart
... Show MoreThis research addresses the necessity due to the scarcity of historical studies in the field of sports, especially those indicating the activities and achievements of Arab countries in the Paralympic movement. This study aims to document the participation of Arab countries in the Paralympic Games, explore the prominent sports in which Arab athletes with disabilities participated, and analyze their achievements during the Paralympic Games from 2004 to 2012. The research methodology adopted an analytical, historical approach, collecting and analyzing data objectively through the official website of the International Paralympic Committee, in addition to scientific and historical sources from research papers, journals, and websites. The key fi
... Show MoreThis research came to shed light on the relationship between the requirements of (practices) high commitment management (participative decision making،information sharing، training and development،team working،rewards،selective staffing،job security ) and strategic entrepreneurship dimensions (entrepreneurial culture،entrepreneurial leadership،entrepreneurial mindset، strategic management resources ) Sought to achieve the number of goals the knowledge and applied, and tested the relationship and impact between variables in a sample size of 100 directors of personnel departments and divisions and their associates in the Iraqi contractors in Baghdad (Hamorabi، Mutassim، AL Rasheed، AL Mansour )، focused research
... Show MorePrecise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables
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