This paper concerns with openness concept in contemporary learning environment, which ranges from physical characters to its relation with learning efficiency and its output. Previous literatures differ to clear the effect of openness on the engagement between learner within themselves, and with this kind of spaces. Engagement means: active participation, the ability of making dialogue, self-reflection and the ability to explore and communicate with them and
within learning space. Research roblem was: The lack of knowledge about the effect of Openness on learner engagement with learning spaces. The two concepts were applied on three types of learning spaces in the Department of the Architecture in the University of Technology, according to their measurements. The research found that there are two types of engagment, positive and negative, that effect of openness in learning space, as increasing of the openness in learning
space as more of the positive engagement of the learner, offset by a decrease in the negative engagement which cause conditions of the boredom and loss of concentration and scattering the learner mind - within this kind of space.
Investments in shares represent an essential component of companies’ assets and a source of profit making resources. These investments are linked to the areas of trading and speculation, which is reflected on their market value, which makes accounting for and evaluating these investments require their own accounting standards, and thus several international standards were issued regarding this as well as a statement of their impact on growth Sustainable, as the research problem is to show the impact of measuring investments in shares according to international accounting and financial reporting standards on the sustainable growth of economic units, the research sample and its reflection on audit procedures. In accordance with i
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The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti
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One of the main environmental problems which affect extensively the areas in the world is soil salinity. Traditional data collection methods are neither enough for considering this important environmental problem nor accurate for soil studies. Remote sensing data could overcome most of these problems. Although satellite images are commonly used for these studies, however there are still needs to find the best calibration between the data and real situations in each specified area. Landsat satellite (TM & ETM+) images have been analyzed to study soil pollution (Exacerbation of salinity in the soil without the use of abandoned agricultural for a long time) at west of Baghdad city of Iraqi country for the years 1990, 2001 & 2007. All of the th
... Show MoreSheet piles are necessary with hydraulic structures as seepage cut-off to reduce the seepage. In this research, the computational work methodology was followed by building a numerical model using Geo-Studio program to check the efficiency of using concrete sheet piles as a cut-off or reducer for seepage with time if the sheet piles facing the drawdown technique. Al-Kifil regulator was chosen as a case study, an accurate model was built with a help of observed reading of the measuring devices, which was satisfactory and helped in checking the sheet piles efficiency. Through the study, three scenarios were adopted (with and without) drawdown technique, it was found that at the short time there's no effect of the drawdown technique on
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The accumulation of sediment in reservoirs poses a major challenge that impacts the storage capacity, quality of water, and efficiency of hydroelectric power generation systems. Geospatial methods, including Geographic Information Systems (GIS) and Remote Sensing (RS), were used to assess Dukan Reservoir sediment quantities. Satellite and reservoir water level data from 2010 to 2022 were used for sedimentation assessment. The satellite data was used to analyze the water spread area, employing the Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) to enhance the water surface in the satellite imagery of Dukan Reservoir. The cone formula was employed to calculate the live storag
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