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 information were collected for a specific period and put into a specific data set. That data was used to find the value of energy consumption in the building using artificial intelligence and data analysis. A Python library called Scikit-learn is used to implement machine learning algorithms. In particular, the Multi-layer Perceptron regressor (MLPRegressor) algorithm was used to predict the consumption. The importance of this work lies in predicting the amount of energy consumed. The outcomes of this work can be used to predict the energy consumed by any building before it is built. The used methodology shows the ability to predict energy performance in educational buildings using previous results and train the model on them, and prediction accuracy depends on the amount of data available for the training in artificial intelligence (AI) steps to give the highest accuracy. The prediction was checked using root-mean-square error (RMSE) and coefficient of determination (R²) and we arrived at 0.16 and 0.97 for RMSE and R², respectively.
The evacuated tube solar collector ETC is studied intensively and extensively by experimental and
theoretical works, in order to investigate its performance and enhancement of heat transfer, for Baghdad climate
from April 2011 till the end of March 2012. Experimental work is carried out on a well instrumented collector
consists of 16 evacuated tubes of aspect ratio 38.6 and thermally insulated tank of volume 112L. The relation
between convective heat transfer and natural circulation inside the tube is estimated, collector efficiency, effect of
tube tilt angles, incidence angle modifier, The solar heating system is investigated under different loads pattern (i.e
closed and open flow) to evaluate the heat loss coefficient
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This study introduces a series of single and pile group model tests subjected to lateral loads in . multilayered sand from Karbala, Iraq. The aim of this study is to investigate: the performance of the pile groups subjected to lateral loads; in which the pile batter inclination angle is changed; the effect of pile spacing (s/d) ratio, the influence of using different number of piles and pile group configuration. Results revealed that the performance of single negative (Reverse) Battered piles with inclination of 10° and 20° show a gain of 32% and 76 % in the ultimate lateral capacity over the regular ones. For pile groups, the use of a combination of regular, negative and positive battered piles in
... Show MoreGenerally, direct measurement of soil compression index (Cc) is expensive and time-consuming. To save time and effort, indirect methods to obtain Cc may be an inexpensive option. Usually, the indirect methods are based on a correlation between some easier measuring descriptive variables such as liquid limit, soil density, and natural water content. This study used the ANFIS and regression methods to obtain Cc indirectly. To achieve the aim of this investigation, 177 undisturbed samples were collected from the cohesive soil in Sulaymaniyah Governorate in Iraq. Results of this study indicated that ANFIS models over-performed the Regression method in estimating Cc with R2 of 0.66 and 0.48 for both ANFIS and Regre
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The rapid advancements in wireless technology and digital electronics have led to the widespread adoption of compact, intelligent devices in various aspects of daily life. These advanced systems possess the capability to sense environmental changes, process data, and communicate seamlessly within interconnected networks. Typically, such devices integrate low-power radio transmitters and multiple smart sensors, hence enabling efficient functionality across wide ranges of applications. Alongside these technological developments, the concept of the IoT has emerged as a transformative paradigm, facilitating the interconnection of uniquely identifiable devices through internet-based networks. This paper aims to provide a comprehensive ex
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To detect the amount of Rifampicin in bulk and medicinal dosage formulations, an accurate, and cost-effective UV spectrophotometric technique has been developed using the area under the peak to estimate the presence of Rifampicin. This range of wavelengths (300–356) nm was chosen. The method showed linearity in the 2-22 μg/mL range, with R2 being 0.9996. The developed method' linearity, detection limit, quantification limit, precision, repeatability, and accuracy were all statistically and experimentally validated. The suggested methodology can be used for routine quality control analysis of Rifampicin in pure form and in capsule dosage form, as demonstrated by the satisfactory recovery percentage results. This study explores the struct
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The rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which ca
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