A substantial percentage of the world’s energy consumption (almost 40%) and carbon dioxide (CO2) emissions (around 37%) come from the construction industry, especially schools. This work presents a new hybrid artificial intelligence (AI) engineering model that aims to maximize energy performance on campuses in a holistic way. Modules for data-driven forecasting, metaheuristic optimization, and real-time adaptive control are all part of the concept. A thorough energy simulation of a university campus building is used in conjunction with the AI model to assess its performance through a co-simulation framework. Findings show that yearly peak electricity demand may be reduced by 18.7% and total site energy consumption by 22.4% when co

Background: The strategy for eliminating measles from Iraq includes conducting mass immunization campaign against measles, within the framework of the national strategic plan for the elimination of this disease. Awareness about this campaign is fundamental for their success.Objective: The study aims at finding out the knowledge, attitudes and practices regarding vaccination against measles among two groups of students in two different colleges ( medical and engineering) .To report uptake of Measles vaccine and reasons for declining the vaccine among medical and non-medical students in the campaignMethod: Across sectional study has been conducted at Al-Kindy College of Medicine/ Baghdad University and University of Technology for the peri

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

Lung cancer is the most common dangerous disease that, if treated late, can lead to death. It is more likely to be treated if successfully discovered at an early stage before it worsens. Distinguishing the size, shape, and location of lymphatic nodes can identify the spread of the disease around these nodes. Thus, identifying lung cancer at the early stage is remarkably helpful for doctors. Lung cancer can be diagnosed successfully by expert doctors; however, their limited experience may lead to misdiagnosis and cause medical issues in patients. In the line of computer-assisted systems, many methods and strategies can be used to predict the cancer malignancy level that plays a significant role to provide precise abnormality detectio

Manual fruit picking is labor-intensive and can damage fruit. Fully mechanized picking is efficient, but it also risks fruit damage. Therefore, semi-automated tools are needed to improve bitter orange picking. This paper presents a smart manual picker designed to facilitate picking while predicting fruit maturity based on picking force as well as various chemical and physical parameters using machine learning (ML). The study methodology consists of five stages: (1) manufacturing the smart picker, (2) picking 50 bitter orange samples, (3) measuring the characteristics of the bitter oranges in the laboratory, (4) training different ML models, and (5) identifying the most accurate model for predicting fruit maturity. The results indicate that

In this study, from a total of 856 mastitis cases in lactating ewes, only 34 Streptococcus agalactiae isolates showed various types of resistance to three types of antibiotics (Penicillin, Erythromycin and Tetracycline). St. agalactiae isolates were identified according to the standard methods, including a new suggested technique called specific Chromogenic agar. It was found that antibiotic bacterial resistance was clearly identified by using MIC-microplate assay (dilution method). Also, by real-time PCR technique, it was determined that there were three antibiotics genes resistance ( pbp2b, tetO and mefA ). The high percentage of isolate carried of a single gene which was the Tetracycline (20.59%) followed by percentage Penicillin was

The research aimed to measure the reality of monetary policy and its role in neutralizing the impact of fluctuations in total domestic oil prices, through the most important monetary policy variable (money supply). An example of this is using a simple technique in the previous example, turning it into a straightforward user interface by (Judd and Kunee). After estimating the impact of the policy with the domestic gross domestic oil prices in Iraq, the effect of fluctuations in the domestic gross domestic oil prices in the simple regression model, while the morale of oil prices was not proven with a negative sign, while the morale of money supply and their impact on the increase of the domestic was proven in the multiple regressio

The Quality  function deployment (QFD)  tool is an important  tool of total quality management because its a link between two important parts customer and production process of the product, using advanced House of quality, which contributed to provide more details about improving the product before it had a vision for the future of the product be improved. Also the identification of the two competitors (Alwazeer , Altouri) bases on the survey of retailers  which they identified five competitors products (Alwazeer , Altouri , Ferry , Jif , Dina)for the product (Zahi). Then House of quality  to product (Zahi) has been developed  By using a Kano Model  to classify of customer's requirements for the

Background: The skull offers a high resistance of adverse environmental conditions over time, resulting in the greater stability of the dimorphic features as compared to other skeletal bony pieces. Sex determination of human skeletal considered an initial step in its identification. The present study is undertaken to evaluate the validity of 3D reconstructed computed tomographic images in sex differentiation by using craniometrical measurements at various parts of the skull. Materials and Method: 3D reconstructed computed tomographic scanning of 100 Iraqi subject, (50 males and 50 females) were analyzed with their age range from20-70 years old. Craniometrical linear measurements were located and marked on both side of the 3D skull images.