As long as the place in which a person lives has a meaning and temporal dimensions , memory is the main axis of these dimensions , today , city centers and old historical sectors of cities are abandoned , and began to turn into slums , the contradiction between old and historical sectors led cities to lose their identity while people lost their sense of belongingness to the old sectors where their ancestors used to live . The old city of Hilla used to have social , historical and cultural role on determining the identity . The study problem can be summarized as the ( lack of studies regarding the impact of historical memory related to Hilla old city on social and cultural mobility ) , the study hypothesis claims that the social , historical and cultural values of the old city of Hilla can have a role in the future development , The aim of the study was to demonstrate on the role of memory in social and cultural mobility and how it is reflected in human spatial urban pattern memories in forming an image of the future and to clarify the relationship between memory and city planning in order to understand the future plans response to human crises and to reach urban and cultural spaces related to memories . The study concluded that the historical memory regarding Hilla old city and historical sectors has and effect and clear role in social and cultural mobility and recommends that this roles can be invested in the process of Planning new sectors in the city.
In this paper, we will illustrate a gamma regression model assuming that the dependent variable (Y) is a gamma distribution and that it's mean ( ) is related through a linear predictor with link function which is identity link function g(μ) = μ. It also contains the shape parameter which is not constant and depends on the linear predictor and with link function which is the log link and we will estimate the parameters of gamma regression by using two estimation methods which are The Maximum Likelihood and the Bayesian and a comparison between these methods by using the standard comparison of average squares of error (MSE), where the two methods were applied to real da
... Show MoreA group of acceptance sampling to testing the products was designed when the life time of an item follows a log-logistics distribution. The minimum number of groups (k) required for a given group size and acceptance number is determined when various values of Consumer’s Risk and test termination time are specified. All the results about these sampling plan and probability of acceptance were explained with tables.
The study aimed to analyze the relationship between the internal public debt and the public budget deficit in Iraq during the period 2010–2020 using descriptive and analytical approaches to the data of the financial phenomenon. Furthermore, to track the development of public debt and the percentage of its contribution to the public budget of Iraq during the study period. The study showed that the origin of the debt with its benefits consumes a large proportion of oil revenues through what is deducted from these revenues to pay the principal debt with interest, which hinders the development process in the country. It has been shownthat although there was a surplus in some years of study, it was not
... Show MoreThe research tackles the potential challenged faced the translator when dealing with the literal translation of nowadays political terms in media. Despite the universal complexity of translating political jargon, adopting literal translation introduces an added layer of intricacy. The primary aim of literal translation is to maintain faithfulness to the original text, irrespective of whether it is in English or Arabic. However, this method presents several challenges within the linguistic and cultural dimensions. Drawing upon scholarly sources, this article expounds upon the multifaceted issues that emerge from the verbatim translation of political terms from English into Arabic. These problems include political culture, language differenc
... Show MoreIn the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn
... Show MoreThe aim of this study is to shed light on the importance of biofuels as an alternative to conventional energy, in addition to the importance of preserving agricultural crops, which are the main source of this fuel, to maintain food security, especially in developing countries. The increase in global oil prices, in addition to the fear of global warming, are among the main factors that draw the world’s attention to searching for alternative sources of traditional energy, which are sustainable on the one hand, and on the other hand reduce carbon emissions. Therefore, the volume of global investment in renewable energy in general, and in liquid biofuels and biomass in particular, has increased. Global fears emerged that the excessive convers
... Show MoreThis work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it
... Show MoreDeep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to
... Show MoreThe fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi
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