The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting

Objective: To evaluate the functional outcomes after extended curettage and reconstruction using a combination of bone graft and bone cement (sandwich). Methodology: In this prospective case series 16 skeletally mature patients with primary giant cell tumor around the knee were included. Patients with previous surgically treated, malignant transformation, degenerative knee changes and those presenting with pathological fracture were excluded. The tumor was excised with bone graft filling space beneath the articular cartilage and a block of gel foam was placed over the cortical surface of picked bone graft. Remaining cavity was filled with polymethylmethacrylate cement (sandwich) with or without internal fixation. The func tional evaluation

The Ground Penetrating Radar (GPR) is frequently used in pavement engineering
for road pavement inspection. The main objective of this work is to validate
nondestructive, quick and powerful measurements using GPR for assessment of subgrade
and asphalt /concrete conditions. In the present study, two different antennas
(250, 500 MHz) were used. The case studies are presented was carried in University
of Baghdad over about 100m of paved road. After data acquisition and radar grams
collection, they have been processed using RadExplorer V1.4 software
implementing different filters with the most effective ones (time zero adjustment and
DC removal) in addition to other interpretation tool parameters.
The interpretatio

The Next-generation networks, such as 5G and 6G, need capacity and requirements for low latency, and high dependability. According to experts, one of the most important features of (5 and 6) G networks is network slicing. To enhance the Quality of Service (QoS), network operators may now operate many instances on the same infrastructure due to configuring able slicing QoS. Each virtualized network resource, such as connection bandwidth, buffer size, and computing functions, may have a varied number of virtualized network resources. Because network resources are limited, virtual resources of the slices must be carefully coordinated to meet the different QoS requirements of users and services. These networks may be modifie

The aesthetic and technical expertise help  in producing the artistic work and achieving results in aesthetic formulations that reflect the aesthetic and  expressive dimensions and the reflective dimensions of the pottery, surpassing its traditions, asserting  its active presence in life, cherishing it  even when it  breaks  or get damaged   by employing techniques that are originated  from  the Japanese environment.

                       The research problem is to study how ( Kintsugi) technique and similar techniques are used to create  new rebirths of pottery piec

Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe