In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and the plasticity index of the soil.
Background: Hand, foot, and mouth disease is viral disease caused commonly by coxsackie virus A16 virus. It is a mild disease and children usually recover with no specific treatment within 7 to 10 days. Rarely, this illness may be associated with aseptic meningitis were patient may need hospitalization.
Objective: To determine significance of clinical features of hand, foot and mouth disease.
Methods: A cross sectional study of cases with clinical features of hand, foot and mouth disease visiting the dermatological consultation unit of Al Kindy teaching hospital. Sampling was for Zyona and Edressi Quarter patients over the period of 1st December 2017
... Show MoreAbstract The aim of this research is to show the grade of implementation of ISO 26000 (Social Responsibility Standard), specifically which related in clause sex (consumer issues), this study was achieved in Market Research and Consumer Protection Center (MRCPC) / University of Baghdad. The seven consumer issues of ISO 26000 was analyzed to show the extent of its implementation in MRCPC depending of using a check list as a principle instrument to collect research data and information. Results analysis was achieved by percentages and mean average. The research was leaded some of results and the most importance one was that the grade of implementation of the center in related to consumer issues given in the standard was medium
Community detection is useful for better understanding the structure of complex networks. It aids in the extraction of the required information from such networks and has a vital role in different fields that range from healthcare to regional geography, economics, human interactions, and mobility. The method for detecting the structure of communities involves the partitioning of complex networks into groups of nodes, with extensive connections within community and sparse connections with other communities. In the literature, two main measures, namely the Modularity (Q) and Normalized Mutual Information (NMI) have been used for evaluating the validation and quality of the detected community structures. Although many optimization algo
... Show MoreThis study uses load factor and loss factor to determine the power losses of the electrical feeders. An approach is presented to calculate the power losses in the distribution system. The feeder’s technical data and daily operation recorded data are used to calculate and analyze power losses.
This paper presents more realistic method for calculating the power losses based on load and loss factors instead of the traditional methods of calculating the power losses that uses the RMS value of the load current which not consider the load varying with respect to the time. Eight 11kV feeders are taken as a case study for our work to calculate load factor, loss factor and power losses. Four of them (F40, F42, F43 and F
... Show MoreThe aim of this research is to study the extent of the impact of government funding decisions on the financial performance of the directorate of Diyala province. The research problem was based on the financial reality of the directorate, and the data were collected from the financial divisions, planning and follow-up, implementation, and engineers of the resident engineer departments. Demonstrate the impact of government funding decisions on financial performance. Using scientific methods in estimating their financial needs through the annual estimated budget. The use of financial analysis to assess the performance of the Directorate, for the purpose of assessing the financial situation of the Directorate of research. The researc
... Show MoreIndustrial development has recently increased, including that of plastic industries. Since plastic has a very long analytical life, it will cause environmental pollution, so studies have resorted to reusing recycled waste plastic (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, producing environmentally friendly load-bearing concrete masonry units (blocks) was considered where five concrete mixtures were compressed at the blocks producing machine. The cement content reduced from 400 kg/m3 (B-400) to 300 kg/m3 (B-300) then to 200 kg/m3 (B-200). While (B-380) was produced using 380 kg/m3 cement and 20 kg/m3 nano-sil
... Show MoreEnglish has for long been one of the most widely used media of communication globally, especially in the Malaysian universities. It has been termed as a Lingua Franca because it is shared with other languages which are considered first languages by different speakers. For this reason, English as a Lingua Franca (ELF) has attracted a number of researchers to investigate its variety via other languages in various communities. The objective of this paper is therefore to establish the strategies which are employing by the international students at the National University of Malaysia/ UniversitiKebangsaan Malaysia (UKM) as an example of one of the Malaysian universities; when they e
... Show MoreDeep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
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