Atomic Force Microscope is an efficient tool to study the topography of precipitate. A study using Continuous Flow Injection via the use of Ayah 6SX1-T-2D Solar cell CFI Analyser . It was found that Cyproheptadine –HCl form precipitates of different quality using a precipitating agent's potassium hexacyanoferrate (III) and sodium nitroprusside. The formed precipitates are collected as they are formed in the usual sequence of forming the precipitate via the continuous flow .The precipitates are collected and dried under normal atmospheric pressure. The precipitates are subjected to atomic force microscope scanning to study the variation and differences of these precipitates relating them to the kind of response to both precipitates give

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

Thermal conductivity measurement was done for specimens of Polystyrene/ titanium dioxide, Polycarbonate/ titanium dioxide and Polymethylmetha acrylate/ titanium dioxide composites for weight ratio of 1.9/ 0.1 and 1.8/ 0.2 wt% for different thickness of the samples. The experimental results show that the thermal conductivity is increased with the increasing of thickness of layers and with the weight ratio of TiO2

In this research study theory to find the stress and emotion gases in the glass as a result of exposure to pulses of the laser beam has been the study using vehicles three major on-system axes cylindrical (r, 0, z), where I took three models of glass silica glass soda glass fused and shedtwo types of lasers where the study showed that the thermal stresses and emotions ...

Some biological aspects of the zebra mussel, Dreissena polymorpha have been studied at Al-Musayab thermal power plant ,sixty km. south west of Baghdad. Data collected during the period extended from November, 2002 to October, 2003 except for the month of April The population consisted of five age groups; O, I, II, III, and IV which have 0, 1, 2, 3 and 4 annuli respectively. The study also proved the validity of annuli readings for age and growth determination. The average annual growth rates for age groups O,I, II, III, and IV were 5.7, 5.5, 5.4, 5.2 and 5.4 respectively. Average calculated length for laboratory reared mussel was 2.5 mm compared to 5.4 mm in natural environment. Correlation coefficients were very high between age an

To evaluate the bioactivity and the cytocompatibility of experimental Bioglass-reinforced polyethylene-based root-canal filling materials. The thermal properties of the experimental materials were also evaluated using differential scanning calorimetry, while their radiopacity was assessed using a grey-scale value (GSV) aluminium step wedge and a phosphor plate digital system. Bioglass 45S5 (BAG), polyethylene and Strontium oxide (SrO) were used to create tailored composite fibres. The filler distribution within the composites was assessed using SEM, while their bioactivity was evaluated through infrared spectroscopy (FTIR) after storage in simulated body fluid (SBF). The radiopacity of the composite fibres and their thermal properties were

The software-defined network (SDN) is a new technology that separates the control plane from data ‎plane for the network devices. One of the most significant issues in the video ‎surveillance system is the link failure. When the path failure occurs, the monitoring center cannot receive the ‎video from the cameras. In this paper, two methods are proposed to solve this problem.  The first ‎method uses the Dijkstra algorithm to re-find the path at the source node switch. The second method ‎uses the Dijkstra algorithm to re-find the path at the ingress node switch (or failed link).

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to