Determination of ligand position in aspartic proteases by correlating tanimoto coefficient and binding affinity with root mean square deviation

Determination of Exponential Smoothing Constant to Minimize Mean Square Error and Mean Absolute Deviation

Exponential smoothing technique is one of the most important quantitative techniques in forecasting. The accuracy of forecasting of this technique depends on exponential smoothing constant. Choosing an appropriate value of exponential smoothing constant is very crucial to minimize the error in forecasting. This paper addresses the selection of optimal value of exponential smoothing constant to ...

Synthesis and Structure Determination of Novel Derivative of Cyclotriphosphazene with Phloroglusine Ligand with Two Protected Position

In this study, we have been involved in the synthesis and characterization studies of a new cyclotriorganophosphazenes complex with protected phloroglusine ligand. Firstly,we synthesized hexachlorocyclotirphosphazene from ammonium chloride and phosphorus pentachloride reaction and then two hydroxyl groups of the phloroglusine ligand were protected with methyl iodide and tosyl chloride. Fina...

On Weighted Pcm and Mean Square Deviation

Optimization of xenon-enhanced CT studies: beam energy, enhancement, root mean square deviation, and repeatability.

The effects of varying beam energy on the computed tomographic (CT) enhancement-to-noise (S:N) ratio were studied experimentally with the DeltaScan 2020 and GE 8800 CT scanners and a 20-cm-diameter cyclindrical Plexiglas phantom containing 11 50 ml syringes filled with varying amounts of xenon and iodine. Enhancements of 54.2, 36.7, and 31.7 Hounsfield units (H)/mg l/ml were measured with the D...

Distributed average consensus with least-mean-square deviation

We consider a stochastic model for distributed average consensus, which arises in applications such as load balancing for parallel processors, distributed coordination of mobile autonomous agents, and network synchronization. In this model, each node updates its local variable with a weighted average of its neighbors’ values, and each new value is corrupted by an additive noise with zero mean. ...