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 objective of the present work is to measuring the concentration of heavy elements (Pb, Cd, Zn, As) in Baghdad's soil city and indication to the probable sources of pollution as well as comparing the concentration of heavy elements with local and international ranges. The Sampling and analyzing conducted in the present work included ( 15 ) Samples from Baghdad city ( three samples for each location ).The rates of heavy elements in soil samples were as following:. Pb ( 67.5 ) ppm, Cd ( 4.11 ) ppm , Zn ( 77.9 ) ppm , As ( 4.64 ) ppm. According to the results, we find increasing in the concentrations of the heavy elements ( Pb, Cd, Zn ) in soils and decreasing in ( As ).We conclude that the main reason behind the in
... Show More
(5)
Background: Hodgkin's lymphoma (HL), formerly called Hodgkin's diseases is an uncommon form of lymphoma. The incidence of Hodgkin's lymphoma shows marked heterogeneity with respect to age, gender, race, geographic area, social class and histological subtype. This study was carried out in an attempt to evaluate the incidence of Hodgkin's lymphoma of head and neck in Baghdad city. Materials and Methods: The diagnosed cases of Hodgkin's lymphoma of head and neck region in Baghdad city between (1990-1999) were collected and analyzed according to age, gender, site and the histopathological subtypes of the tumor. Results: Out of (702) cases of Hodgkin's lymphoma of ten years between (1990-1999),(362 ) of them were occurred in the head and neck
... Show MoreSeveral studies have indicated that more than 600 cities in the world (intermas of rapid growth and development) will generate about 60% of international economic growth between 2010 and 2025 . by 2025 , 66% of the worlds population will live in urban areas the management of cities will face challenges that accompany this increase in the population which requires preparing to face these challenges and problems and the need to provide the aim of the research to know the readiness of Baghdad city to implement the strategies of urban management throught on asmple representing the ( Advisiry group for the comprechnsive development plan for the city of Baghdad 2030 and its supporters ) in the municipality of Baghdad and the number of
... Show More
In this study 737 stool specimens were collected from people attending some primary health care centres and hospitals in North of Baghdad, during the period from beginning of April 2009 till the end of March 2010. Different factors were examined to be related with the prevalence of Cryptosporidiosis which were (number of family member, travelling history, source of drinking water and domestic animal present). Significant relations (p≤0.05) were observed between infection rate and the following factor: -Number of family member: The high percentage of Cryptosporidium spp positive cases were seen in families composed of (15-19) and (more than 20) individual which were 28.32% and 16.37% respectively when compared with other family clusters -T
... Show More
(7)
The aim of this research is to explore the time and space distribution of traffic volume demand and investigate its vehicle compositions. The four selected links presented the activity of transportation facilities and different congestion points according to directions. The study area belongs to Al-Rusafa sector in Baghdad city that exhibited higher rate of traffic congestions of working days at peak morning and evening periods due to the different mixed land uses. The obtained results showed that Link (1) from Medical city intersection to Sarafiya intersection, demonstrated the highest traffic volume in both peak time periods morning AM and afternoon PM where the demand exceeds the capacity along the link corridor. Also, higher values f
... Show MoreGround water hydrochemical study in Yusufiyah depends upon (25) wells where major cations and anions were obtained as well as trace elements. The hydrochemical properties include the study of (pH, EC, TDS, and TH). The groundwater of the study area is odorless and colorless except the wells (13 and 16) with a salty taste due to the elevated (TDS) concentration in it, where the wells depth ranges between 7-20 meters. Depth of water in these wells was about 25-35 meters above sea level. Groundwater generally flows from east to west and from north east to south west. The resource of groundwater depends upon surface water. Physical specifications are measured in the water samples included temperature, color, taste, odor, pH, electrical condu
... Show More
(1)
Deep Learning Techniques For Skull Stripping of Brain MR Images
(1)
One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p
... Show More
(1)
In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A
... Show More
(2)
(1)
Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutil
... Show More
(15)
(15)
