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

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

  This work intends to illustrate the methods of using the authentic literary text in the process of spreading Italian, especially in Baghdad where there is a strong propensity to learn the Italian language. The concept of the language that arises from literature is an idea closely linked to the mentality of the Arab learner towards Italian culture: an idea also created by the first Arabisations of literary texts in the early years of the previous century. The research was carried out in Baghdad by two researchers, an Italianist from Baghdad and an Italian mother language linguist, with the aim of bringing together the two sectors in favor of the diffusion of the Italian language. The study also aims to clarify the models from Italian l

The research aims to apply a modified SERVQUAL model to evaluate the quality of the educational services via conducting exploratory research for students from the College of Administration and Economics- Department of Business Administration- Evening studies at the University of Baghdad. Questionnaire of two parts was distributed to a sample of (72) students out of (720) students of the 2^nd.,3^rd. and 4^th. year in the beginning of the second semester of the year 2008-2009 to measure the expectations and perceptions to the quality of the educational services. Five major dimensions were analyzed to see the gaps for (22) variables. The study concluded that there were (13) variables confirmed that the

يعتقد البعض ان مفهوم العلم يعني الآلات والاجهزة العلمية (تقنيات التعليم) وهي لا تختلف عن مفهوم تكنولوجيا المعلومات , ويعد هذا الاعتقاد خاطئ , لان العلم هو بناء المعرفة العلمية المنظمة والتي يتم التوصل اليها عن طريق البحث العلمي , اما تكنولوجيا المعلومات فهي "التطبيقات العملية للمعرفة العلمية في مختلف المجالات ذات الفائدة المباشرة بحياة الانسان, او هي النواحي التطبيقية للعلم وما يرتبط بها من آلات واجهزة".