The normality test was investigated as an initial different step in process capability studies for better results and higher accuracy. Considering normality tests, the results indicated that all of the data and distributions were close to expected values under normality. The variables include enzyme amount, reaction time, reaction temperature, substrates molar ratio, and agitation speed. Quadratic mathematical model was suggested for synthesis of TEA-based esterquat. Analysis of variance corroborates the accuracy of the model by using high F value (33.60), very low P value (<0.0001), nonsignificant lack of fit, and the coefficient of determination (R2 = 0.9201). A conversion percentage of 63.57% was attained, which was good compared to the predicted amount of 65.08%, with the relative standard error percentage (RSE) 2.
32%. The comparison of RSM and ANN (QP) indicated that the RSM had less RSE% rather than ANN (QP) method (3.98%). The methodology as a whole has proven that RSM is adequate for the design and optimization of the enzymatic process.AcknowledgmentThe financial assistance provided by Universiti Putra Malaysia under the Research University Grant Scheme (RUGS) is gratefully acknowledged.
In wireless ad hoc networks, it is known that transmissions over wireless channels suffer from radio propagation loss, shadowing, fading, radio interference, and limited bandwidth. Moreover, there are also effects from traffic patterns which can degrade certain links if the network control is not traffic aware.
Therefore, a lot of research attempts have been made in every layer and even across layers to improve the performance of communications in ad hoc networks. However, most improvements consider only the existing problems and lack the flexibility towards emerging problems, especially the highly focused cross-layer optimization becomes less extensible and difficult to maintain .Traditional network control mechanisms often rely on a certain set of predefined rules and fine-tuned parameters for known situations. However, computer network architectures and their protocols have become increasingly sophisticated over time through addition of many features to support new applications, where different applications may require different settings of protocol parameters.
Since the total number of possible situations occurring in the real world is too numerous to be handled by preprogrammed sets of definitions, it is necessary that new networking mechanisms are designed in a flexible and adaptive manner to cater for any changes in the Drug_discovery environment.In an attempt to design new adaptive networking methods, concepts based on biological mechanisms have been proposed [2, 3] for self-organized control since they are able to provide greater robustness and adaptability to external influences. The core idea is to derive a protocol that is based on the model of a natural phenomenon.