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To test validity and evaluate the performance of the TAVT model, we designed three experiments in this section.
Using this model we designed a hardware accelerator for an image reconstruction algorithm for biomedical application.
Based on the ROBIN model, we designed and implemented tag recommendation algorithm named ROBIN-T.
Besides, with the help of the ES model, we designed a new transfer algorithm for BTNs.
Based upon our model, we designed a general architecture for collaborative creativity applications.
Instead of the traditional linear model, we designed an Artificial Neural Network (ANN) to fit the data.
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Hence, for each of the presented models we designed various methods to obtain data by providing certain parameters.
We derived statistical signal models of RF impairments, and based on the statistical signal models, we designed estimators of RF impairments.
Contaminated area datasets with varying shapes should be tested to assess the efficiency of the geo-processing models we designed with other type of pollution coverage (and shapes).
On the basis of the steric contour maps of the models, we designed four new compounds in the 2,4-diamino-5-methyl-6-phenylsulfanyl-substituted 2,4-diamino-5-methyl-6-phenylsulfanyl-substituted 2,4-diamino-5-methyl-6-phenylsulfanyl-substituted 2,4-diamino-5-methyl-6-phenylsulfanyl-substituted 2,4-diamino-5-methyl-6-phenylsulfanyl-substituted 2,4-diamino-5-methyl-6-phenylsulfanyl-substituted 2,4-diamino-5-methyl-6-phenylsulfanyl-substituted pyrrolo[2,3-d]pyrimidine pyrrolo[2,3-d]pyrimidine
Using computational modeling, we designed the dendrimer scaffold and protein attachment point to resemble the native N-glycan architecture.
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