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Developing a Model to Estimate the Productivity of Ready Mixed Concrete Batch Plant
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Productivity estimating of ready mixed concrete batch plant is an essential tool for the successful completion of the construction process. It is defined as the output of the system per unit of time. Usually, the actual productivity values of construction equipment in the site are not consistent with the nominal ones. Therefore, it is necessary to make a comprehensive evaluation of the nominal productivity of equipment concerning the effected factors and then re-evaluate them according to the actual values.

In this paper, the forecasting system was employed is an Artificial Intelligence technique (AI). It is represented by Artificial Neural Network (ANN) to establish the predicted model to estimate wet ready mixed concrete (WRMC) plant production and dry ready mixed concrete (DRMC) plant production, in addition to determining the factors affecting productivity.

The results showed that the artificial intelligence neural network is an effective technique to estimate the productivity of the dry and wet ready mixed concrete batch plant. The ANN model showed satisfying results of validation for both training and external datasets with the range of training dataset and poor results with the data that exceeds the range of training. At the same time, the skills of the operators, frequent failure of concrete, and lack of construction materials were the most important factor that affected productivity.

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Publication Date
Tue Apr 18 2023
Journal Name
Corporate Reputation Review
The Absorptive Capacity of Knowledge as an Approach for Building Strategic Reliability in the Sponge Organizations/Small Organizations in Kirkuk Governorate as a Model
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Publication Date
Sat Apr 09 2022
Journal Name
Engineering, Technology & Applied Science Research
A Semi-Empirical Equation based on the Strut-and-Tie Model for the Shear Strength Prediction of Deep Beams with Multiple Large Web Openings
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The behavior and shear strength of full-scale (T-section) reinforced concrete deep beams, designed according to the strut-and-tie approach of ACI Code-19 specifications, with various large web openings were investigated in this paper. A total of 7 deep beam specimens with identical shear span-to-depth ratios have been tested under mid-span concentrated load applied monotonically until beam failure. The main variables studied were the effects of width and depth of the web openings on deep beam performance. Experimental data results were calibrated with the strut-and-tie approach, adopted by ACI 318-19 code for the design of deep beams. The provided strut-and-tie design model in ACI 318-19 code provision was assessed and found to be u

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Publication Date
Tue Apr 01 2014
Journal Name
Al-nahrain Journal Of Science
Formation of Polymeric Assemblies of Six-Coordinate Metal Complexes with Mixed Bridges of Dicarboxylato-Azido
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New polydentate ligand namely bis(N-carboxylatoethyl)-0,0`-dipyridinium) L was synthesised from the reaction of 0,0`-dipyridine with ethyl chloropropionate. Polymeric complexes of general formulae [Cr2(L)(N3)0]Cl2.H2O, Na2[Ag2(L)(N3)0].H2O and [M2(L)(N3)0].nH2O, where (M= Mn(II), Fe(II), Co(II), Ni(II), Cu(II), Zn(II) and Cd(II); (where n = 2;1;1;1;4;1 and 1, respectively)) are reported. The mode of bonding and overall geometry of the complexes were determined through physico-chemical and spectroscopic methods. These studies revealed octahedral geometry complexes. Molecular structure for the complexes has been optimised by CS Chem 3D Ultra Molecular Modelling and Analysis Program and supported a six coordinate geometry.

Publication Date
Fri Sep 01 2017
Journal Name
Ce/papers
16.15: Experimental evaluation of a novel demountable shear connector for accelerated repair or replacement of precast steel‐concrete composite bridges
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A novel demountable shear connector for precast steel‐concrete composite bridges is presented. The connector uses high‐strength steel bolts, which are fastened to the top flange of the steel beam with the aid of a special locking nut configuration that prevents slip of bolts within their holes. Moreover, the connector promotes accelerated construction and overcomes typical construction tolerances issues of precast structures. Most importantly, the connector allows bridge disassembly, and therefore, can address different bridge deterioration scenarios with minimum disturbance to traffic flow, i.e. (i) precast deck panels can be rapidly uplifted and replaced; (ii) connectors can be rapidly removed and replaced; and (iii) steel beams can b

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Publication Date
Mon Mar 15 2021
Journal Name
Al-academy
Aesthetic Levels in Shape Variables in Spectacular Films the Indian Film (Main Tera Hero) a Model: غسان محسن حمد
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The spectacular film is a type of feature films which has specific elements that contribute in increasing the aesthetics of the shape in its structure. The researcher started studying this type of films by researching the spectacular film concept, the history of its development, who are its most important stars and then tackling the Indian cinema represented by Bollywood, which is considered a school for this type of film. The researcher addressed the most important influential elements that entre in its production as well as studying these elements that contribute to building the shape including the configuration, movements of cameras, lenses, the lighting, colors, costumes etc. and what influence they have in forming a special aestheti

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Publication Date
Sun Jun 11 2017
Journal Name
Al-academy
Regularity Relations Signals According Pillars Expressive Between the Narrator and Narrative Discourse Alcinmatugrave Legend Movie In 1900 A Model
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This study is concerned with the concept of offering a point of view as a narrative construction element, especially the element and point of view of the novel to the letter Alcinmatugrave both business taken from masterpieces and literary works in the foundation or set of cinema. On the whole, the narrator participate in mock narrative process and support the narrator visual image, especially stories that need to exist scenes prove added to the image that uses signs of reality to take those marks a new dimension not only across the image, but also the intervention of the narrator in the re-formation of this realism marks surrounding Palms perceived and visible and put markers regularly between what the narrative of privacy and image, fo

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Publication Date
Wed Dec 01 2021
Journal Name
Structures
The effect of ground motion characteristics on the fragility analysis of reinforced concrete frame buildings in Australia
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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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Publication Date
Tue Sep 10 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A classification model on tumor cancer disease based mutual information and firefly algorithm
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