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

In this study, the synoptic analysis of dust storm for spring and summertime in Iraq were investigated. The images for dust provided by NASA are used to emphasize the dust storm days, while the composite maps of wind vector and geopotential 850hPa are mapped to investigate the pressure and wind direction patterns appearing with the dust condition in the same days. Spring has more dust frequency than summertime, especially in May. The frontal type of dust storm is dominant on spring, the cold air pushes the warm air that picking up the sand to the air through the vertical wind, but the southwestern high-speed wind and drought condition were controlled on the dust in summer. The northwestern wind is the main factor that carries the dust for l

Dust storms are a natural phenomenon occurring in most areas of Iraq. In recent years, the study of this phenomenon has become important because of the danger caused by increasing desertification at the expense of the green cover as well as its impact on human health. In this study  is important to devote the remote sensing of dust storms and its detection.Through this research, the dust storms can be detected in semi-arid areas, which are difficult to distinguish between these storms and desert areas. For the distinction between the dust storm pixels in the image with those that do not contain dust storm can be applied the Normalized Difference Dust Index (NDDI) and Brightness Temperature variation (BTV). MODIS sensors that carried

The actual observations for Jupiter radio storm were taken for Hawaii station within multi years from 2001 to 2012. The Central Meridian Longitude (CML_ІІІ) and Io's phase (γ_Io) were calculated for each year from Radio Jove program, the results of CML_ІІІ for year 2006 was A=(180-300)º,B=(15-239)º, C=(60-280)º, phase was A=(182-260)º,B=(40-109)º, C=(200-260)º, which were close to the theoretical values, longitude was A=(180-300)º, B=(15-240)º, C=(60-280)º and phase was A=(180-260)º,B=(40-110)º and C=(200-260)º.

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

Magnetic plaster kiln dust (MPKD) was synthesized as a unique, low-cost composite reused of byproduct plaster kiln dust (PKD), which is considered a source of air pollution. The FESEM, EDS, XRD, FTIR, VSM, and BET tests were used to characterize the MPKD. The characterization revealed that the MPKD was nanotubes non-agglomerated and super-paramagnetic with a high specific surface area (102.7 m²/g). Compared with the specific area of other materials (composites), the MPKD could be considered a promising substance in the field of water/wastewater treatment.

Plastic soil exhibits unfavorited geotechnical properties (when saturation), which causes negative defects to engineering structures. Different attempts (included various materials) were conducted to proffer solutions to such defects by experimenting in practical ways. On one hand, these attempts aimed to improve the engineering characteristics of plastic soil, and on the other hand, to use problematic waste materials as a stabilizer, like cement kiln dust, and to reduce environmental hazards. This paper explored the shrinkage, plasticity, and strength behavior of plastic soil enhanced with cement dust. The cement dust contents were 0%, 5%, 10%, 15% and 20% by dry weight of soil. An experimental series of shrinkage and p

The ionospheric characteristics exhibit significant variations with the solar cycle, geomagnetic conditions, seasons, latitudes and even local time. Representation of this research focused on global distribution of electron (Te) and ion temperatures (Ti) during great and severe geomagnetic storms (GMS), their daily and seasonally variation for years (2001-2013), variations of electron and ion temperature during GMS with plasma velocity and geographic latitudes. Finally comparison between observed and predicted Te and Ti get from IRI model during the two kinds of storm selected. Data from satellite Defense Meteorological Satellite Program (DMSP) 850 km altitude are taken for Te, Ti and plasma velocity for different latitudes during great