The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

Abstract Background The aim of this study was to identify differences in oral cancer incidence among sexes, age groups and oral sites over time in Iraqi population. Methods Data was obtained from Iraqi cancer registry, differences and trends were assessed with the Wilcoxon matched-pairs signed-ranks test and Regression test, respectively. Results In Iraq from 2000 to 2008, there were 1787 new cases of oral cancer registered, 1035 in men and 752 in women. Cancer at all oral sites affected men more than women. The Tongue other (ICD-02) is the most frequent site follow by lip (ICD-00). Conclusion The decrease in the percent of oral cancer incidence in Iraq not compatible with the high percent of exposure to the risk factors, Iraqi cancer regis

This article investigates Iraq wars presentation in literature and media. The first section investigates the case of the returnees from the war and their experience, their trauma and final presentation of that experience. The article also investigates how trauma and fear is depicted to create an optimized image and state of fear that could in turn show Iraqi society as a traumatized society. Critics such as Suzie Grogan believes that the concept of trauma could expand to influence societies rather than one individual after exposure to trauma of being involved in wars and different major conflicts. This is reflected in Iraq as a country that was subjected to six comprehensive conflicts in its recent history, i.e. less than half a century; th

In this study, two correlations are developed to calculate absolute rocks permeability from core samples tested by Gas Permeameter Apparatus. The first correlation can be applied if K g≤100, the second correlation can be applied if Kg>100. Sixty core samples having different permeabilities to give a wide range of values that necessary to achieve a correlation.

The developed correlation is easily applied and a quick method to avoid repeating the test at different pressure values. Only one pressure test is required to reach absolu

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Staphylococcus Sp.is the most common type of bacteria found in contamination place, we design this
study to compare the contamination accident between two hospitals in Baghdad.One of them isthe Burns
Specialist Hospital in the Medical CityinRusafa and another one is Al-Karama Hospital in Karkh. The
samples were collected fromOperativeWard No1 (OW1), Operative Ward No2 (OW2), Consulting Pharmacy
(CP), Emergency Room (ER), Reception Room (RR), Women's Ward (WW) and Men's Ward (MW).The
samples were taken from inside each clinical unit, surfaces, food, and air. The results showed that the
number of samples containing Staphylococcus sp. bacteria is 81, including 45 belonging to Al-Karama Burns
Ward Ho

This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att