Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postponement of delay of interim payments is at the forefront of delay factors caused by the employer’s decision. Even the least one is to leave the job site caused by the contractor’s second part of the contract, the repeated unjustified stopping of the work at the site, without permission or notice from the client’s representatives. The developed model was applied to about 97 projects and used as a prediction model. The decision tree model shows higher accuracy in the prediction.
The research aims to study the basic concepts of the underwriting policy with its various indicators. The researcher studies the underwriting policy with its various indicators (sex, health status, age of the insured, insurance amount, The method of acceptance, payment method, and duration of insurance) where each of these indicators constitute an important factor in the productivity of life insurance policies, where the productivity of life insurance policies face many difficulties because insurance is a service and not a tangible material commodity and its benefits and not current. Therefore, the life insurance company needs to use a prudent underwriting policy so as not to endanger its financial position due to the expansion of the un
... Show MoreImage processing applications are currently spreading rapidly in industrial agriculture. The process of sorting agricultural fruits according to their color comes first among many studies conducted in industrial agriculture. Therefore, it is necessary to conduct a study by developing an agricultural crop separator with a low economic cost, however automatically works to increase the effectiveness and efficiency in sorting agricultural crops. In this study, colored pepper fruits were sorted using a Pixy2 camera on the basis of algorithm image analysis, and by using a TCS3200 color sensor on the basis of analyzing the outer surface of the pepper fruits, thus This separation process is done by specifying the pepper according to the color of it
... Show MoreThe reality of the field of construction projects in Iraq refers to needing for the development of performance in order to improve quality and reduce defects and errors and to control the time and cost, so there is needing for the application of effective methods in this area, one of the methods that can be applied in this area is the manner of Six Sigma. This research aims to enhance the performance and quality improvement for the construction projects by improving performance in the work of the implementation of the concrete structure depending on the Six Sigma methodology, and for the purpose of achieving the aim of the research, the researcher firstly depends on the theoretical study that include the concepts of qual
... Show MoreThe avoidance of failure in construction projects is not an easy task, which makes the failure of the construction project to achieve its objectives a major problem experienced by all countries in the world, especially Iraq. Where nearly two-thirds of the construction projects in the world have been suffered by significant problems as an increase in the cost of the project, delay in the specified duration for execution, and stopping the project. Therefore it is required to study and apply new methods for managing the construction project to ensure its success and achieve its objectives. The aim of this study is to study the Agile project management method and its impact on the construction project. In addition, to identi
... Show MoreLandSat Satellite ETM+ image have been analyzed to detect the different depths of regions inside the Tigris river in order to detect the regions that need to remove sedimentation in Baghdad in Iraq Country. The scene consisted of six bands (without the thermal band), It was captured in March ٢٠٠١. The variance in depth is determined by applying the rationing technique on the bands ٣ and ٥. GIS ٩. ١ program is used to apply the rationing technique and determined the results.
We have studied Bayesian method in this paper by using the modified exponential growth model, where this model is more using to represent the growth phenomena. We focus on three of prior functions (Informative, Natural Conjugate, and the function that depends on previous experiments) to use it in the Bayesian method. Where almost of observations for the growth phenomena are depended on one another, which in turn leads to a correlation between those observations, which calls to treat such this problem, called Autocorrelation, and to verified this has been used Bayesian method.
The goal of this study is to knowledge the effect of Autocorrelation on the estimation by using Bayesian method. F
... Show More<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c
... Show MoreAbstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition
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