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Genetic Algorithms in Construction Project Management: A Review
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Genetic algorithms (GA) are a helpful instrument for planning and controlling the activities of a project. It is based on the technique of survival of the fittest and natural selection. GA has been used in different sectors of construction and building however that is rarely documented. This research aimed to examine the utilisation of genetic algorithms in construction project management. For this purpose, the research focused on the benefits and challenges of genetic algorithms, and the extent to which genetic algorithms is utilised in construction project management. Results showed that GA provides an ability of generating near optimal solutions which can be adopted to reduce complexity in project management and resolve difficult problems associated with multi-modal, noisy, high dimensional and discrete functions. However, with a range of benefits, there are multiple challenges as well such as GA can be time consuming to restore the images and may provide partial solution to the problem.

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Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
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Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Mining categorical Covid-19 data using chi-square and logistic regression algorithms
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Publication Date
Tue May 16 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Comparative Study of Anemia Classification Algorithms for International and Newly CBC Datasets
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Data generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
The Role Of Smart Leadership Dimensions In Crisis Management- A study For Opinions Of Sample Of Administrative Leaderships In A number Of Humanities Colleges At The University Of Mosul
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This research aims at answering many questions raised by the research problem concerning the view of the organizations under consideration for the concept of smart leadership and its most important dimensions, as well as the view of crisis management and its concept and most important methods through research objectives that define and clarify the smart leadership with its dimensions and methods of crisis management.

For the purpose of reaching the results of the research and testing the assumptions about the relationship between smart leadership and methods of crisis management, the researcher adopted a questionnaire, designed especially to be a criterion for the research, as the main tool for data coll

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Publication Date
Thu Feb 01 2024
Journal Name
Journal Of Engineering
Evaluating the Knowledge for Integrating RM and VM Using BIM in the Iraqi Construction Sector
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The construction industry plays a crucial role in the countries' economy, especially in the developed country. This point encourages the concerned institution to use new techniques and integrate many techniques and methods to maximize the benefits. The main objective of this research is to evaluate the use of risk management, value management, and building information modeling in the Iraqi construction industry. The evaluation process aims at two objectives. The direct objective was to evaluate the knowledge in risk management (RM), value management (VM), and building information modeling (BIM). The indirect objective was to support the participants with information related to the main items mentioned. The questionnaire

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Publication Date
Sun Jan 01 2023
Journal Name
4th International Conference On Distributed Sensing And Intelligent Systems (icdsis 2023)
EcoSavvy: revolutionizing waste management in smart cities
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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Medical waste management in Al-Kut City
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This research investigates solid waste management in Al-Kut City. It included the collection of medical and general solid waste generated in five hospitals different in their specialization and capacity through one week, starting from 03/02/2012. Samples were  collected and analyzed periodically to find their generation rate, composition, and physical properties. Analysis results indicated that generation rate ranged between (1102 – 212) kg / bed / day, moisture content and density were (19.0 % - 197 kg/ m3) respectively for medical waste and (41%-255 kg/ m3) respectively for general waste. Theoretically, medical solid waste generated in Al-Kut City (like any other city), affected by capacity, number of patients in a day, and hosp

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Facial Emotion Images Recognition Based On Binarized Genetic Algorithm-Random Forest
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Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

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Publication Date
Mon Jan 28 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Managerial Skills and It`s Role in Strengthening the Competitive Edge of Companies: A Case Study in the General Company for Construction Industries
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This research tries to reveal how to manage and control the competitive edge for business by building managerial skills in various organizational levels. Our research aims at finding out the nature of various technical, human and in tellectual skills of a new president whose superiority is his competitive ness in the application field at general company for construe tioual  industriesand testing the surveyed minor and major changes through a questionnaire to collect information from officials. The sample was composed of (45) director. The data was analyzed  using some methods and statistical programs. The most prominent of these is (SPSS) that was used to extract the arithmetic mean, standard deviation, correlation coefficient

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Publication Date
Sun Jun 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Gas Lift Optimization for Zubair Oil Field Using Genetic Algorithm-Based Numerical Simulation: Feasibility Study
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The gas-lift method is crucial for maintaining oil production, particularly from an established field when the natural energy of the reservoirs is depleted. To maximize oil production, a major field's gas injection rate must be distributed as efficiently as possible across its gas-lift network system. Common gas-lift optimization techniques may lose their effectiveness and become unable to replicate the gas-lift optimum in a large network system due to problems with multi-objective, multi-constrained & restricted gas injection rate distribution. The main objective of the research is to determine the possibility of using the genetic algorithm (GA) technique to achieve the optimum distribution for the continuous gas-lift injectio

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