Due to the easily access to the satellite images, Google Earth (GE) images have become more popular than other online virtual globes. However, the popularity of GE is not an indication of its accuracy. A considerable amount of literature has been published on evaluating the positional accuracy of GE data; however there are few studies which have investigated the subject of improving the GE accuracy. In this paper, a practical method for enhancing the horizontal positional accuracy of GE is suggested by establishing ten reference points, in University of Baghdad main campus, using different Global Navigation Satellite System (GNSS) observation techniques: Rapid Static, Post-Processing Kinematic, and Network. Then, the GE image for the study area was captured, saved, and georefrenced based on precise positions for ten selected reference points. The findings of this research indicate that the network method gives the most accurate results than using other two methods. Closer inspection of the results shows that the network method enhanced the results in comparison with the results of Rapid Static and PPK in the east component by 50% and 60%, respectively and in the north component by 18% and 20%, correspondingly.
Objective: This study aims to examine how implementing Extensible Business Reporting Language (XBRL) enhances the efficiency and quality of environmental audits and sustainability reporting in eco-friendly universities. Aligned with Sustainable Development Goal 12 (Responsible Consumption and Production), the study emphasizes promoting transparency and precision in sustainability reporting to encourage responsible management of resources within academic institutions. Theoretical Framework: The importance of our study is evident in the importance of accurate and transparent reports in the development of environmental performance with theories of sustainable reporting and environmental auditing. One of the most important digital
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Abstract
The current research aims to identify mental health and its role in promoting self-confidence and positive behavior of female university students. The researcher adopted the descriptive analytical approach in this research. The researcher depended on the availability of sources and references, literature, and previous field studies to analyze and study all aspects related to mental health and its role in promoting self-confidence and positive behavior of university students and then expand its importance and identify the areas of mental health, self-confidence, positive behavior, and university. The second chapter included the concept of mental health, the importance of the study, the most important factors of health and psyc
Abstract: Despite the distinct features of the continuous wave (CW) Terahertz (THz) emitter using photomixing technique, it suffers from the relatively low radiation output power. Therefore, one of effective ways to improve the photomixer emitter performance was using nanodimensions electrodes inside the optical active region of the device. Due to the nanodimension sizes and good electrical conductivity of silver nanowires (Ag-NWs), they have been exploited as THz emitter electrodes. The excited surface plasmon polariton waves (SPPs) on the surface of nanowire enhances the incident excitation signal. Therefore, the photomixer based Ag-NW compared to conventional one significantly exhibits higher THz output signal. In thi
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay
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The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.
Was conducted to compare the two methods above and it became clear by comparing the logistic regression model best of a Linear Discriminant function written
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This work represents study the rock facies and flow unit classification for the Mishrif carbonate reservoir in Buzurgan oil Field, which located n the south eastern Iraq, using wire line logs, core samples and petrophysical data (log porosity and core permeability). Hydraulic flow units were identified using flow zone indicator approach and assessed within each rock type to reach better understanding of the controlling role of pore types and geometry in reservoir quality variations. Additionally, distribution of sedimentary facies and Rock Fabric Number along with porosity and permeability was analyzed in three wells (BU-1, BU-2, and BU-3). The interactive Petrophysics - IP software is used to assess the rock fabric number, flow zon
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