Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

The tax system, like any other system, as a set of elements and parts that complement each other and are interrelated and interact to achieve specific goals, and is a natural  reflection of the economic, social and political conditions prevailing in society, and therefore the objectives of tax policy formulated in line with the objectives of economic policy in general, which means that any change in economic policy clearly affects fiscal policy measures and fiscal policy in particular.

The problem of searching for the impact of foreign direct investment in the Iraqi tax system was focused on the study  the of foreign direct investment and therole played in developing and improving the economic reality and its implicatio

The research seeks to highlight the importance of digital finance in banking by providing financial and banking services and its role in improving the access of financial services to customers at the farthest possible point by using modern technology to finance their needs by granting them cash credits through electronic payment tools to facilitate them and shorten time and effort as well as Low cost, and this cannot be achieved without concerted efforts and the provision of basic infrastructure that includes connecting the Internet to all targeted areas, whether cities or rural areas, as well as distributing the largest possible number of ATMs and sending specialized teams to those areas that develop in customers the culture of digital

In drilling processes, the rheological properties pointed to the nature of the run-off and the composition of the drilling mud. Drilling mud performance can be assessed for solving the problems of the hole cleaning, fluid management, and hydraulics controls. The rheology factors are typically termed through the following parameters: Yield Point (Yp) and Plastic Viscosity (μp). The relation of (YP/ μp) is used for measuring of levelling for flow. High YP/ μp percentages are responsible for well cuttings transportation through laminar flow. The adequate values of (YP/ μp) are between 0 to 1 for the rheological models which used in drilling. This is what appeared in most of the models that were used in this study. The pressure loss

paid recent developments in the information and communications technology and the accompanying developments in the global market to pay particular accounting information users to demand more sophistication in terms of corporate financial reporting systems, which led to the emergence of a new type of reporting (financial reporting in real time). where is the information and communications technology mainstay Nations for the development and progress, thanks to the development of technology that have made the transmission of information easily conducted and high speed to all who need it, communication is instantaneous and the flow of information via the internet dramatically exceeded the border temporal and spatial anywhere in the w

    Two dwarf snakes were discovered, Eirenis thospitis Schmidtler & Lanza from Sereen mountain, north east of Arbil  and E. rothii Jan from Saffin mountain North of Arbil  city  North of Iraqi Kurdistan. Supported by description and important notes on variation. In addition summarized list for 9 species of the genus Eirenis Jan in Iraq is also presented.  

These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that.  The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce

BACKGROUND: Volar Barton’s fracture is a shearing mechanism of injury that results in fracture and subluxation of distal end radius in which volar rim of the distal radius is displaced with hand and carpus. Open reduction and volar plate fixation ensure more stable change of displacement, preservation of reduction, and early mobilization. AIM: This study aims to assess the functional and radiological outcome results of volar Barton’s fracture treated by volar buttress plate using the demerit points system of Gartland and Werley. PATIENTS AND METHODS: This study is a prospective descriptive observational study on 32 patients who were treated with ORIF by volar buttress plate for isolated volar Barton’s fractures between Fe

In this paper, thermal performance of a zig-zig solar air heater (ZZSAH) with and without using steel wire mesh on the absorber plate of the collector is experimentally investigated. The experimental work includes four inclination angles of the collector 20^o, 30^o, 45^o, and 60^o and four air mass flow rates of 0.03, 0.04, 0.06, and 0.08 kg/s under varieties of operating conditions of a geographic location of  Baghdad. New correlation equations of Nusselt number are obtained from experimental results for both types of collectors where the effect of varying of the inclination angle of collector taken into consideration in the experiment. The correlations show good agreement wi

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In