Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

Soils at Al-Koot-Btera were choosen to determine their sedimentary
environments. It is found that there are , five soil series and as mentioned :
MF11-MW9-DM97-DM57-DF95 . The five found soil series are of internal
well drained ,moderate and imperfect. Their textures vary in moderately,fine
and moderately fine.
indicating that sediments rang from poorly to very poorly sorting. Values of median
diameter Md Ø range between 4.11-7.80 Ø .The relation between the sorting
and median diameter shows that 95.24% of samples is a sedimentary
environment of aquite river , while 4.76% is aeolian sediments.
The values of meso to platy kurtic of most horizon materials rang
between 0.67-1.26 Ø .That is to say the samples

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

This research was aimed to study the exposure of Razzazah Lake  to major hydrological changes in recent years as a result of natural climatic changes  and  drought, high evaporation in lake due to stop discharge from Habbaniyah Lake  by Al- majera channel. During 2019, we collected surface water samples at three locations, and three samples from groundwater, in addition one samples from each location Imam Ali Drop and Sewage water  of Karbala. The Results  show that the heavy isotopes in lake and groundwater well are enriched during the warm period, and depleted during the cold period. Chemically, The dominant cations and anions in Al-Razzaza lake water are mainly of in Order  Ca > Na > Mg and  Cl>SO4 and the water

study was conducted on a stretch of Tigris river crossing Baghdad city to determine the concentration of some chlorophenols pollutants. Aqueous samples were preliminary enriched about 500 times and the chlorophenols have determined using high performance liquid chromatography HPLC. Limits of detection LOD were (0.007–0.012 mg L-1), relative standard deviations RSD% were 2.4%–5.59% and relative recoveries were 51.06%– 104.07%. The existence of chlorophenols in Tigris river was in the range 0.023–4.596 mg L-1. The developed method suggested in this study can be applied for routine analysis and monitoring of chlorinated phenols in environmental aqueous samples.

Due to the deliberate disposal of industrial waste, a great amount of petroleum hydrocarbons pollute the soil and aquatic environments. Bioremediation that depends on the microorganisms in the removal of pollutants is more efficient and cost-effective technology. In this study, five rhizobacteria were isolated from Phragmites australis roots and exposed to real wastewater from Al-Daura refinery with 70 mg/L total petroleum hydrocarbons (TPH) concentration. The five selected rhizobacteria were examined in a biodegradation test for seven days to remove TPH. The results showed that 80% TPH degradation as the maximum value by Sphingomonas Paucimobilis as identified with Vitek® 2 Compact (France).

It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i

Khadija Al-Hadithi was known for her love of the Arabic language. She was a distinguished and serious phenomenon in Arabic science and culture. She was born in Basra Governorate, one of the ancient and important cities in the history of Arabic grammar and one of the centers of the intellectual and scientific movement. The Basra Grammar School emerged there and made numerous achievements in the field of Arabic linguistics that remain an important source for students of the specialty.