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Identificatio n Of Key Factors Affecting Waste Management In Life Cycle Of The Construction Project By Using Delphi Technique
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The problem of generated waste as a result of the implementation of construction projects, has  been aggravated recently because of construction activity experienced by the world, especially Iraq, which is going through a period of reconstruction, where construction waste represents (20-40%) of the total generated waste and has a negative effect on the environment and economic side of the project. In addition, the rate of consumpted  amounts of natural resources are estimated to be about 40% in the construction industry, so it became necessary to reduce waste and to be manage well. This study aims to identify the key factors affecting waste management through the various phases of the project, and this is accomplished by using the Delphi technique. After conducting three questionnaire rounds of the Delphi to a group of experts, the results of this study identified forty four key factors affecting waste management distributed on the phases of the project, where found that the factor of frequent errors in the designs has the highest effect on the design phase, and the factor of the use of construction techniques that do not generate waste has highest effect on the construction phase. The purpose is to provide data base for decision-makers to control waste management well to avoid all affecting factors, with the possibility of building waste management system based on factors effective for each phase.

 

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Preparing Nanosilica Particles from Rice Husk Using Precipitation Method
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Nanosilica was extracted from rice husk, which was locally collected from the Iraqi mill at Al-Mishikhab district in Najaf Governorate, Iraq. The precipitation method was used to prepared Nanosilica powder from rice husk ash, after treating it thermally at 700°C, followed by dissolving the silica in the alkaline solution and getting a sodium silicate solution. Two samples of the final solution were collected to study the effect of filtration on the purity of the sample by X-ray fluorescence spectrometry (XRF). The result shows that the filtered samples have purity above  while the non-filtered sample purity was around  The structure analysis investigated by the X-ray diffraction (XRD), found that the Nanosilica powder has an amorphous

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
3D scenes semantic segmentation using deep learning based Survey
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Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po</p> ... Show More
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Publication Date
Thu Feb 25 2016
Journal Name
Research Journal Of Applied Sciences, Engineering And Technology
Block Matching Algorithm Using Mean and Low Order Moments
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In this study, a fast block matching search algorithm based on blocks' descriptors and multilevel blocks filtering is introduced. The used descriptors are the mean and a set of centralized low order moments. Hierarchal filtering and MAE similarity measure were adopted to nominate the best similar blocks lay within the pool of neighbor blocks. As next step to blocks nomination the similarity of the mean and moments is used to classify the nominated blocks and put them in one of three sub-pools, each one represents certain nomination priority level (i.e., most, less & least level). The main reason of the introducing nomination and classification steps is a significant reduction in the number of matching instances of the pixels belong to the c

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Speech Signal Compression Using Wavelet And Linear Predictive Coding
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A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen level and ignored details coefficients, and then approximation coefficients are windowed by a rectangular window and fed to the linear predictor. Levinson Durbin algorithm is used to compute LP coefficients, reflection coefficients and predictor error. The compress files contain LP coefficients and previous sample. These files are very small in size compared to the size of the original signals. Compression ratio is calculated from the size of th

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Publication Date
Wed Mar 23 2011
Journal Name
Ibn Al- Haitham J. For Pure & Appl. Sci.
Image Compression Using Proposed Enhanced Run Length Encoding Algorithm
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In this paper, we will present proposed enhance process of image compression by using RLE algorithm. This proposed yield to decrease the size of compressing image, but the original method used primarily for compressing a binary images [1].Which will yield increasing the size of an original image mostly when used for color images. The test of an enhanced algorithm is performed on sample consists of ten BMP 24-bit true color images, building an application by using visual basic 6.0 to show the size after and before compression process and computing the compression ratio for RLE and for the enhanced RLE algorithm.

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Computers, Communications, Control And Systems Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

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Publication Date
Wed Apr 28 2021
Journal Name
2021 1st Babylon International Conference On Information Technology And Science (bicits)
Enhanced Twitter Community Detection using Node Content and Attributes
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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Scheduling projects using dynamic programming style and smart algorithm
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The aim of this research is to compare traditional and modern methods to obtain the optimal solution using dynamic programming and intelligent algorithms to solve the problems of project management.

It shows the possible ways in which these problems can be addressed, drawing on a schedule of interrelated and sequential activities And clarifies the relationships between the activities to determine the beginning and end of each activity and determine the duration and cost of the total project and estimate the times used by each activity and determine the objectives sought by the project through planning, implementation and monitoring to maintain the budget assessed 

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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials &amp; Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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Publication Date
Mon Jan 02 2017
Journal Name
European Journal Of Scientific Research
Fast approach for arabic text encryption using genetic algorithm
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As s widely use of exchanging private information in various communication applications, the issue to secure it became top urgent. In this research, a new approach to encrypt text message based on genetic algorithm operators has been proposed. The proposed approach follows a new algorithm of generating 8 bit chromosome to encrypt plain text after selecting randomly crossover point. The resulted child code is flipped by one bit using mutation operation. Two simulations are conducted to evaluate the performance of the proposed approach including execution time of encryption/decryption and throughput computations. Simulations results prove the robustness of the proposed approach to produce better performance for all evaluation metrics with res

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