The Yemen Kings and gaverners allered notable services to the pilgrims, who
were in their way to perform the pilgrimage to Mecca. Among them Al-Hysen Ibn
Salama (dead 384, Aih). The governer of Al- Zeadiea state, who concern about
pilgrimage route from its beginning at Hudrumot to its end at Mecca Al Makruma, the
distant was estimated by 60th days to pass the way he also eastablished asystem of
water “artesian wells” as long as the pilgrimage way also setting up large Mosqeses
and Marking out the way of the caravans of pilgrimage to save these caravans from
lossing the right way, he setting up under ground water chanal started from Arafat to
holy Mecca in order to ensure water supplies for the erea. This proje

MA Mahde, HAA Kadhim, HN Tarish…, Pakistan Heart Journal, 2023 - Cited by 4

Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

Classifying butterfly species is crucial in biodiversity studies and environmental monitoring. However, manual classification is often a laborious process that requires specialized expertise and is prone to error, especially when species have similar visual characteristics. To address these drawbacks, this paper presents a hybrid approach that combines machine learning with deep learning for feature extraction. To enhance the visibility of important features, preprocessing techniques such as background removal and binarization are applied to butterfly images. Feature extraction was performed using the SqueezeNet convolutional neural network, pretrained on the ImageNet dataset. By discarding the final classification layer, the networ

The self-evident truth existing in today's business environment is the continuity of change and its continuity and turmoil, also its increase over time as it is more abundant, abundant, wide and complex than ever before, and it is the dominant feature in the business environment, as different organizations and operating units can find themselves shifting from the top to the bottom. And then it requires its departments to strive to adapt to these rapid and turbulent shifts and changes by bringing about a series of organizational and adaptive changes that are not limited to one organizational aspect only but rather include all organizational components. Accordingly, this research came to determine the readiness of public organizations to chan

Abstract :

       The research aims to diagnose some of the negative phenomena
 ( Counterfiting , Pettifogging , Embezzlement ) that have been detected over the past ( 2010 – 2014 ), a fixed-term part of the national strategy for the fight against corruption launched by the Joint Council for the fight against corruption in Iraq and measuring the application of government control according to the American standard GAO standards and identifying the potential for the application of those standards gap. It has been collecting data and information of special issues of corruption reports and meeting with (42) employees and the use of a checklist has been prepared for thi

The present research aims to identify thecorrelation between cognitive motivation andthe trend towards the teaching profession among students of the Department of Chemistry in theFaculty of Education for Pure Sciences - Ibn al-Haytham, as well as to identify the differences in the relationship according to the variable type (male, female). The measures of cognitive motivation and the trend towards the teaching profession were applied, using pearson's correlation coefficient,t-testfor one sample, andthe t-test of two separate samples.

Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul