A study was performed to evaluate heavy metals removal from sewage sludge using lime. The processes of stabilization using alkaline chemicals operating on a simple principle of raising pH to 12 or higher, with sufficient mixing and suitable contact time to ensure that immobilization can reduce heavy metals. A 0.157 m3 tank was designed to treat Al-Rustemeyia wastewater treatment plant sludge. Characteristics of raw sludge were examined through two parameters: pH and heavy metal analysis. Different lime doses of (0- 25) g CaO/100 g sludge were mixed manually with raw sludge in a rotating drum. The samples were analyzed two hours after mixing. pH and heavy metals results were compared with EPA and National Iraqi Stand

     Equilibrium and rate of mixing of free flowing solid materials are found using gas fluidized bed. The solid materials were sand (size 0.7 mm), sugar (size0.7 mm) and 15% cast iron used as a tracer. The fluidizing gas was air with velocity ranged from 0.45-0.65 m/s while the mixing time was up to 10 minutes. The mixing index for each experiment was calculated by averaging the results of 10 samples taken from different radial and axial positions in fluidized QVF column 150 mm ID and 900 mm height.

     The experimental results were used in solving a mathematical model of mixing rate and mixing index at an equilibrium proposed by Rose. The results show that mixing index increases with inc

This study is considered to be the first on this sector of Tigris River after 2003, to evaluate the effect of Tharthar Arm on the composition and diversity of Copepoda in Tigris River. Six sampling sites were selected; two on the Tharthar Arm and four sites along the Tigris River, one before the confluence as a control site and the others downstream the confluence; thirty-five copepod taxa were recorded, 34 taxa in the Tigris River and 25 taxa in the Tharthar Arm.
The highest density of Copepoda was in site 2 at Tharthar Arm was 265584.2 Ind./m3 lead to an increasing in Copepoda density in Tigris River from 63878.2 Ind./m3 in site 1 before the confluence to 127198.3 Ind./m3 in site 4 immediately downstream the confluence. Also, the me

Occurrence the heavy metals in water is one of the most important concerns. may cause savior health problems. In this work we made an attempt to know the quantity of six heavy metals in groundwater in different locations of Baghdad city. Examinations were made on groundwater of the review region to assess the heavy metals. Groundwater samples were gathered and analyzed utilizing Atomic Absorption Spectrophotometer for their Manganese, Iron, Zinc, Cadmium, Copper and Lead content and their levels compared with World Health Organization (WHO) specified maximum contaminant level. In order to accomplish this, water samples were obtained from 10 randomly selected wells in the region, in February and August, 2016. The study showed that the ground

The increasing efficiency of the telecommunications network in the city contributes to the increase in spatial interaction between activities (to influence and mutual influence) This study is based on the idea that the upgrading of telephone services provided to citizens are done exclusively through the growth and development of all levels of the service using advanced technologies to know the problems and appropriate solutions in short time and less cost. Thus, crystallized the objectives of the study which was built for the importance of GIS in the planning of services in general, and infrastructure services, in particular, including telephone services, which is represent a point of contact between individuals on the one hand a

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

Authors in this work design efficient neural networks, which are based on the modified Levenberg - Marquardt (LM) training algorithms to solve non-linear fourth - order three -dimensional partial differential equations in the two kinds in the periodic and in the non-periodic - Periodic. Software reliability growth models are essential tools for monitoring and evaluating the evolution of software reliability. Software defect detection events that occur during testing and operation are often treated as counting processes in many current models. However, when working with large software systems, the error detection process should be viewed as a random process with a continuous state space, since the number of faults found during testin

Back ground: One out of six children in the
world today is involved in child labor, doing
work that is damaging to his or her mental,
physical and emotional development.
Objective: Assessment of some health
problems among the studied working children.
Method; A cross-sectional study was
conducted in Al Amen Primary Health Care
(PHCC) during the period from January to
August 2009, a sample of 6048 children were
selected randomly(3218girls and2866 boys age
between 5-17 years ) and interviewed to collect
information using a structured questionnaire
form, information related to different aspects
of child labor prevention were included in the
form as well as a general medical examination
and lab

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network