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.
This study investigates the influence of fear, refuge, and migration in a predator–prey model, where the interactions between the species follow an asymmetric function response. In contrast to some other findings, we propose that prey develop an anti-predator response in response to a concentration of predators, which in turn increases the fear factor of the predators. The conditions under which all ecologically meaningful equilibrium points exist are discussed in detail. The local and global dynamics of the model are determined at all equilibrium points. The model admits several interesting results by changing the rate of fear of predators and predator aggregate sensitivity. Numerical simulations have been performed to verify our theoret
... Show MoreLung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c
... Show MoreBackground: Whey protein is the green-yellow colored, liquid portion of the milk, and it is also called the cheese serum, it is obtained after the separation of curd, during the coagulation of the milk. It contains a considerable amount of α-helix pattern with an evenly distributed hydrophobic and hydrophilic as well as basic and acidic amino acids along with their polypeptide chain. The major whey protein constituents include β-lactoglobulin (β-LG),α-lactalbumin (α-LA), immunoglobulins (IG), bovine serum albumin (BSA), bovine lactoperoxidase (LP), bovine lactoferrin (BLF) and minor amounts of a glycol macro peptide (GMP). Osseointegration can be defined as a process that is immune driven which leads to the formatio
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Predicting peterophysical parameters and doing accurate geological modeling which are an active research area in petroleum industry cannot be done accurately unless the reservoir formations are classified into sub-groups. Also, getting core samples from all wells and characterize them by geologists are very expensive way; therefore, we used the Electro-Facies characterization which is a simple and cost-effective approach to classify one of Iraqi heterogeneous carbonate reservoirs using commonly available well logs.
The main goal of this work is to identify the optimum E-Facies units based on principal components analysis (PCA) and model based cluster analysis(MC
... Show MoreMachine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed
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Summary
The book (Fatah al-Rahman reveals what is ambiguous in the Qur’an), which is a book of verbal similarities that tries to touch the Qur’an expression, and the subtle differences between its expressions and expressions. It appeared when it appeared in many chapters, from which I chose to delete in monolithic letters such as Ba and Ta, and to heal and delete in non-monosymbols such as (that) and (may) and (no), so the search came to two chapters The first is for deleting the monolithic letters, and the second is for deleting non-monosyllabic letters, preceded by introductory discussions revolving around the linguistic and idiomatic definition of deletion, a brief translation of the
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