The study of human factors and the extent of their impact on the construction of land transport roads is of great importance because they are variable factors, which are on the contrary natural factors, and the impact of human factors on road construction operations is evident through the study of population distribution and size, and economic activities (agricultural, industrial, tourism). And its direct mutual relationship with the construction and extension of land transport routes and the development of each of them, and then directing them to serve urban and rural human settlements, which leads to their development and improvement of their economic, living and social conditions on the one hand, and contributes to the emergence

The research problem was to identify the impact of monetary policies on economic growth in the oil and non-oil countries. The researcher chose the Republic of Iraq as an example for the oil countries and the Arab Republic of Egypt as an example for the non-oil countries to hold a comparison on the impact of monetary policies.

The research found that the monetary policies and their tools in the Iraqi economy affect the rate of GDP growth by 73%, which shows the strong impact of monetary policies on the economic growth in the Iraqi economy as an example of an oil state. GDP growth rate of 61%, indicating the impact of monetary policies on economic growth in the

Background: The preparation of Platelet-rich plasma (PRP) is minimally invasive way, simple, low cost to obtain natural autologous growth factors and is now being widely used in different fields of medicine for its ability to increase the regeneration potential of tissue. The aim of this study was to investigate the effect of local application of autologous PRP gel on acceleration rate of osseointegration period by clinical assessment accomplished by determining the changes in implant stability during 3 months healing period using resonance frequency analysis (RFA). Materials and methods: A total of 28 dental implants were inserted in edentulous maxillae or mandibles of 13 patients using a split mouth design, i.e. each patient was received

The prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traff

The records of Primary Health Care Centres (Al-Risafa section of Baghdad) were inspected for communicable diseases during the period January-April 2006. There were 8622 recorded cases (the diagnosis was based on a clinical examination and laboratory findings), which were distributed as 4782 (55.5%), 1430 (16.6%), 1604 (18.6%) and 806 (9.3%) for Sadar city, Risafa, A'adhamyiah and Mada'in, respectively. The highest frequency was reported for chicken pox (42.7%), followed by mumps and typhoid fever (20 and 13.7%, respectively), while diphtheria and cholera were not recorded. These three most frequent diseases were further analyzed, and their distribution showed a significant difference (P ? 0.001). April was the month of the highest recorded

In this paper solar radiation was studied over a region of Baghdad (Latitude 33.3o and longitude 44.4o). The two parts of global solar radiation: diffuse and direct solar radiation were estimated depending on the clearance index of measured data (Average Monthly mean global solar radiation). Metrological data of measured (average monthly mean diffuse and direct solar radiation) were used to comparison the results and show the agreement between them. Results are determined by applying Liu and Jordan two models (1960). Excel 2007program is used in calculation, graphics and comparison the results.

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a