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Detecting Damaged Buildings on Post-Hurricane Satellite Imagery based on Transfer Learning
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In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performance measures are used as a criterion to decide which classifier is the best one to detect the images with high accuracy. Eventually, the simulation results show that each classifier detect the damage/no damage image with different performance measures and then makes it easy to select the best one.

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Publication Date
Sat Nov 11 2023
Journal Name
مجلة كلية الامام الاعظم
Provisions for inheritance of agricultural lands (transfer of the right to dispose of)
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Agricultural lands have great importance in people's lives, and their exploitation has a great impact on strengthening the national economy. Therefore, countries have given great importance to this sector, and because of the importance of this sector, the state has given large areas of these lands to the farmers to invest in agriculture, and among these farmers are those who died and left behind children who took up crafts. Agriculture, for fear that these agricultural lands would be abandoned and turned into waste lands, a land system was introduced called (regular distribu- tion), which corresponds to (legitimate inheritance). Under this system, these lands were trans- ferred to the children of farmers who died so that the process of inve

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Publication Date
Wed Sep 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Effective Bed Thermal Conductivity and Heat Transfer Coefficient in Fluidized Beds
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Experimental study of heat transfer coefficients in air-liquid-solid fluidized beds were carried out by measuring the heat rate and the overall temperature differences across the heater at different operating conditions. The experiments were carried out in Q.V.F. glass column of 0.22 m inside diameter and 2.25 m height with an axially mounted cylindrical heater of 0.0367 m diameter and 0.5 m height. The fluidizing media were water as a continuous phase and air as a dispersed phase. Low density (Ploymethyl-methacrylate, 3.17 mm size) and high density (Glass beads, 2.31 mm size) particles were used as solid phase. The bed temperature profiles were measured axially and radially in the bed for different positions. Thermocouples were connecte

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Publication Date
Wed Mar 30 2011
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
ESTIMATION OF MASS TRANSFER COEFFICIENTS IN A PACKED DISTILLATION COLUMN USING BATCH MODE
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This research adopts the estimation of mass transfer coefficient in batch packed bed distillation column as function of physical properties, liquid to vapour molar rates ratio (L / V), relative volatility (α), ratio of vapour and liquid diffusivities (DV / DL), ratio of vapour and liquid densities (ρV / ρL), ratio of vapour and liquid viscosities (μV/ μL).
The experiments are done using binary systems, (Ethanol Water), (Methanol Water), (Methanol Ethanol), (Benzene Hexane), (Benzene Toluene). Statistical program (multiple regression analysis) is used for estimating the overall mass transfer coefficient of vapour and liquid phases (KOV and KOL) in a correlation which represented the data fairly well.

KOV = 3.3 * 10-10

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Publication Date
Wed Mar 30 2011
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
PARAMETRIC STUDY OF NATURAL CONVECTIVE AND RADIATIVE HEAT TRANSFER IN INCLINED CYLINDRICAL ANNULI
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The unsteady state laminar mixed convection and radiation through inclined
cylindrical annulus is investigated numerically. The two heat transfer mechanisms of
convection and radiation are treated independently and simultaneously. The outer
cylinder was kept at a constant temperature while the inner cylinder was heated with
constant heat flux. The study involved numerical solution of the governing equations
which are continuity, momentum and energy equations using finite difference method
(FDM), where the body fitted coordinate system (BFC) was used to generate the grid
mesh for computational plane. A computer program (Fortran 90) was built to calculate
the bulk Nusselt number (Nub) after reaching steady state con

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Publication Date
Thu Dec 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Modeling of Mass Transfer Coefficient in Rotating Biological Contactor with Perforated Discs (RPBC)
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Abstract

 In order to make an improvement associated with rotating biological contactor (RBC), a new design of biofilm reactor called as Rotating perforated disc biological contactor (RPBC) was developed in which the rotating discs are perforated. The transfer of oxygen from air to wastewater was investigated. Mass-transfer coefficient (KLa)  in the liquid phase was determined by measuring  the rate transfer of oxygen.  A   laboratory scale of (RPBC) consisted of a semicircular trough was used with a working capacity of 40 liters capacity of liquid. Synthetic wastewater was used as a liquid phase, while air was used as a gas phase.

The effects of m

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Publication Date
Mon Jul 01 2019
Journal Name
International Journal Of Heat And Mass Transfer
Hybrid heat transfer enhancement for latent-heat thermal energy storage systems: A review
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Publication Date
Sun Nov 01 2020
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Utilizing the ATM technology in e-distance learning
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<p>There is an Increasing demand for the education in the field of E-learning specially the higher education, and to keep contiuity between the user and the course director in any place and time. This research presents a proposed and simulation multimedia network design for distance learning utilizing ATM technique. The propsed framework determines the principle of ATM technology and shows how multimedia can be integrated within E- learning conteext. The first part of this research presents a theoretical design for the Electricity Department, university of technology. The purpose is to illustrate the usage of the ATM and Multimedia in distance learning process. In addition, this research composes two entities: Software entity

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Publication Date
Fri Jul 26 2024
Journal Name
Academia Open
Enhancing Pediatric Nursing Skills by Top Learning Strategies
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Background: The efficacy of educational strategies is crucial for nursing students to competently perform pediatric procedures like nasogastric tube insertion. Specific Background: This study evaluates the effectiveness of simulation, blended, and self-directed learning strategies in enhancing these skills among nursing students. Knowledge Gap: Previous research lacks a comprehensive comparison of these strategies' impacts on skill development in pediatric nursing contexts. Aims: The study aims to assess the effectiveness of different educational strategies on nursing students' ability to perform pediatric nasogastric tube insertions. Methods: A pre-experimental design was employed at the College of Nursing, University of Baghdad, i

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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes On Data Engineering And Communications Technologies
Utilizing Deep Learning Technique for Arabic Image Captioning
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Publication Date
Tue Dec 21 2021
Journal Name
Mendel
Hybrid Deep Learning Model for Singing Voice Separation
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Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

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