Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

Research summary

Today, the Islamic nation is going through a phase that is one of the most dangerous that it has never experienced before. This phase was characterized by the following:

The nation is divided into states and its weakness in most of its doctrinal, political, social, economic and moral aspects.
Enemies targeting the nation's faith and capabilities, and the emergence of loyalty to the enemies of the nation from some groups of society, spreading misconceptions in the Muslim community.
Spreading the spirit of rebellion in all segments of society and striving to stir up the people against the rulers and put pressure on the rulers.

All these manifestations and others require the nation's wise men

In this research, we sought to identify the nature of the relationship between the exchange rate of the Chinese yuan and the value of Chinese exports, through the formulation of a standard model based on the model of common integration, and based on the data of the study and using the test "Angel-Granger" It reflects the relationship between the two research variables, through which the relationship between the RMB exchange rate and the value of Chinese exports was estimated during the period 1978-2017.

Thin films ZrO₂: MgO nanostructure have been synthesized by a radio frequency magnetron plasma sputtering technique at different ratios of MgO (0,6, 8 and  10)% percentage to be used as the gas sensor for nitrogen dioxide NO₂. The samples were investigated by X-ray diffraction (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) and sensing properties were also investigated. The average particle size of all prepared samples was found lower than 33.22nm and the structure was a monoclinic phase. The distribution of grain size was found lower than36.3 nm and uninformed particles on the surface. Finally, the data of sensing properties have been discussed, where the

This paper studies the influence of temperature on the corrosion rate of coated AA6111 aluminum alloy used in vehicle bodies under static and vibration states. The vibration test system was collected laboratory and used for testing of five different types of paints (EASI, Numix, Lesonal, DENSO and Polaron paints) in the 5 % NaCl solution using immersion test method. Lesonal paint provided the best corrosion protection, while DENSO paints show large values of corrosion rate, other coatings exhibit moderate values. Model of paints corrosion was developed to characterize the corrosion processes occur at the surfaces. It is found that corrosion rate obtained at vibration cases is larger than static cases and vibration effect

Aims: To assess the success rate and implant stability changes of narrow dental implants (NDIs) during the osseous healing period. Materials and methods: This prospective observational clinical study included 21 patients with narrow alveolar ridge of restricted mesiodistal interdental span who received NDIs. The alveolar ridge width was determined by the ridge mapping technique. Implant stability was measured using Periotest® M immediately after implant insertion then after 4 weeks, 8 weeks and 12 weeks postoperatively. The outcome variables were success rate and implant stability changes during the healing period. The statistical analysis included one-way analysis of variance (ANOVA) and Tukey\'s multiple comparisons test, values < 0.05 w

The present search aims to develop a test for selective attention, cognitive load and thinking mistakes and measuring these concepts among Baghdad university students. To make a comparison between the selective attention, cognitive load, and the mistakes of thinking among students in term of gender. To identify the relationship among the selective attention, cognitive load and the mistakes of thinking of university students. To achieve these purposes, the searcher has developed a test for selective attention, cognitive load, and the mistakes of thinking. Then, these tools were applied to a sample of (200) university students were selected from (21) college. The researcher used t-test of one sample, t-test of two independent