Globally, buildings use about 40% of energy. Many elements, such as the physical properties of the structure, the efficiency of the cooling and heating systems, the activity of the occupants, and the building’s sustainability, affect the energy consumption of a building. It is really difficult to predict how much energy a building will need. To improve the building’s sustainability and create sustainable energy sources to reduce carbon dioxide emissions from fossil fuel combustion, estimating the building's energy use is necessary. This paper explains the energy consumed in the lecture building of the Al-Khwarizmi College of Engineering, University of Baghdad (UOB), Baghdad, Iraq. The weather data and the building construction informati

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

Land Transport regards a main element in the In Fra – structure of the national economy where distance and time shortness, open new opportunities of work, develop the different regions and rise the standard of living….

It is necessary to emphasize that the circumastances surrounding Iraq such as wars, economic sanctions, blockade occupation effected negatively upon economic Indicators of land Transportion including Value of output Value added contraction of Investment allocation and  Investment expend tuer and the period of implementation and fulfillment of the projects of Land Transport to be ready to offer their service in underdeveloped country Like Iraq aiming to satisfy Fast and acomprehensi

An Expression for the transition charge density is investigated
where the deformation in nuclear collective modes is taken into
consideration besides the shell model transition density. The
inelastic longitudinal C2 and C4 form factors are calculated using
this transition charge density for the Ne Mg 20 24 , , Si 28 and S 32
nuclei. In this work, the core polarization transition density is
evaluated by adopting the shape of Tassie model togther with the
derived form of the ground state two-body charge density
distributions (2BCDD's). It is noticed that the core polarization
effects which represent the collective modes are essential in
obtaining a remarkable agreement between the calculated inelastic
longi

Inelastic longitudinal electron scattering form factors have been calculated for isoscaler transition
T = 0 of the (0+ ®2+ ) and (0+ ®4+ ) transitions for the 20Ne ,24Mg and 28Si nuclei. Model
space wave function defined by the orbits 1d5 2 ,2s1 2 and 1d3 2 can not give reasonable result for
the form factor. The core-polarization effects are evaluated by adopting the shape of the Tassie-
Model, together with the calculated ground Charge Density Distribution CDD for the low mass 2s-1d
shell nuclei using the occupation number of the states where the sub-shell 2s is included with an
occupation number of protons (a ) .

This study was done to test the activity of some plant extracts as antioxidant agents. The plants were (Morus rubra, Hibiscus sabdariffa L ., Rhus coriaria L., Anethum graveolens and Petroselinum sativum).
Ethanolic 98% (24 hours/ 25˚c) and distilled water (30 minutes/ 25˚c have been used for extraction.The Total phenols, total flavonoids, total anthocyanin, antioxidant activities were studied.
The extract of Morus rubra was chosen because it has a higher antioxidant activity.
The phenolic extract of Morus rubra was prepare and examined by application it in burger . The antioxidant activity test of Morus rubra was made before and after 3,6 days of cold storage. The sensory evaluation of all treatments were done within 5,1

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al