In this research, a factorial experiment (4*4) was studied, applied in a completely random block design, with a size of observations, where the design of experiments is used to study the effect of transactions on experimental units and thus obtain data representing experiment observations that The difference in the application of these transactions under different environmental and experimental conditions It causes noise that affects the observation value and thus an increase in the mean square error of the experiment, and to reduce this noise, multiple wavelet reduction was used as a filter for the observations by suggesting an improved threshold that takes into account the different transformation levels based on the logarithm of the base and obtaining several values for the suggested threshold and applying then Haar wavelet function With the cut-off hard and mid threshold and Comparing the results according to several criteria.
Diesel generators is widely used in Iraq for the purpose of maintaining electric power demand. Large number of operators engaged in this work encounters high level of noise generated by back pack type diesel generators used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known., in present research , quastionaire was adsministered 86 repondents in Baghdad city were exposured to wide range of noise level (80-110) dB(A) with different ages and they have different skill discretion levels. Noise levels A-weigthed decibles dB(A) were measured over 8 weeks two times aday during the 2019 summer using a sound level meter.For predicting the wo
... Show MoreDiesel generators is widely used in Iraq for the purpose of maintaining electric power demand. Large number of operators engaged in this work encounters high level of noise generated by back pack type diesel generators used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known., in present research , quastionaire was adsministered 86 repondents in Baghdad city were exposured to wide range of noise level (80-110) dB(A) with different ages and they have different skill discretion levels. Noise levels A-weigthed decibles dB(A) were measured over 8 weeks two times aday during the 2019 summer using a sound level meter.For predicting the wo
... Show MoreThe research aimed at measuring the compatibility of Big date with the organizational Ambidexterity dimensions of the Asia cell Mobile telecommunications company in Iraq in order to determine the possibility of adoption of Big data Triple as a approach to achieve organizational Ambidexterity.
The study adopted the descriptive analytical approach to collect and analyze the data collected by the questionnaire tool developed on the Likert scale After a comprehensive review of the literature related to the two basic study dimensions, the data has been subjected to many statistical treatments in accordance with res
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The introduction to the research included a presentation of some physical characteristics and their importance in sports, including the speed of kinesthetic response response and the extent of its usefulness and importance, especially for soccer goalkeepers, as it is the most important element that goalkeepers must have, and it is also the main key to the excellence and development of all physical and kinesthetic response qualities and skills of a goalkeeper. Football. The speed of kinesthetic response response and reaction is one of the requirements of the game of football, as well as all other sports and even in general professional life. Its importance is highlighted for the football goalkeeper, so he must master it perfectly to perform
... Show MoreThis article describes how to predict different types of multiple reflections in pre-track seismic data. The characteristics of multiple reflections can be expressed as a combination of the characteristics of primary reflections. Multiple velocities always come in lower magnitude than the primaries, this is the base for separating them during Normal Move Out correction. The muting procedure is applied in Time-Velocity analysis domain. Semblance plot is used to diagnose multiples availability and judgment for muting dimensions. This processing procedure is used to eliminate internal multiples from real 2D seismic data from southern Iraq in two stages. The first is conventional Normal Move Out correction and velocity auto picking and
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Different ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach
Background: Blood group system and the ability to taste phenylthiocarbamide (PTC) are the most studied traits in human genetics which have been extensively used in describing genetic variations among human populations around the world that may had an effect on dental caries. The aims of present study were to investigate the caries experience among students with different bitter taste threshold in relation to blood type. Materials and Methods: The sample of present study includes dental students female aged19-21 years. The diagnosis of dental caries was done according to the criteria of Manjia et al, 1989 recording decayed lesion by severity (D1-4) MFS. Furthermore, bitter taste sensitivity was measured according to PTC (phenylthiocarbamid
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Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an
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In this study, we focused on the random coefficient estimation of the general regression and Swamy models of panel data. By using this type of data, the data give a better chance of obtaining a better method and better indicators. Entropy's methods have been used to estimate random coefficients for the general regression and Swamy of the panel data which were presented in two ways: the first represents the maximum dual Entropy and the second is general maximum Entropy in which a comparison between them have been done by using simulation to choose the optimal methods.
The results have been compared by using mean squares error and mean absolute percentage error to different cases in term of correlation valu
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