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ABSTRACT: This research compared 2 types of model (regression model and artificial neural network) for prediction of glue content for sealing toothpaste carton from 4 sealing process factors, i.e., production line, diameter of toothpaste tube, pressure in glue nozzle during applying glue onto a toothpaste carton and glue temperature in a glue tank. Models under study included 3 regression models, i.e., multiple regression, polynomial regression and stepwise regression,and backpropagation neural network (BPN). The results indicated that the BPN model possessed higher prediction accuracy and generalization capability and lower bias. The best BPN model had a structure of 4-10-1 with the mean absolute error (MAE) of validating data set of 0.04 gram. In addition, the BPN model identified that the most influential sealing process factors affecting the prediction of glue content were pressure in glue nozzle and glue temperaturein the glue tank. The packing department should concentrate on monitoring the value of both factors to control the consistency of glue usage.12/2015; 3. DOI:10.1016/j.aaspro.2015.01.005
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ABSTRACT: This works mention on improvement of power conversion efficiency of dye-sensitized solar cell by addition of SnO2 into ZnO photoanode. Power conversion efficiency is achieved by reduction of transfer resistance to induce pathway direction for electron transfer in photoanode which observed in term of steady photocurrent density. Dye-sensitized solar cell was fabricated from additive SnO2 weight ratio of 3-9% in ZnO nanoparticles and dissolved into polyethylene glycol solution. SnO2-ZnO composites were prepared on fluorine doped tin oxide glass substrate by doctor blade technique and annealed at 450 ̊C for 1 h. It was found that the SnO2 weight ratio of 7% showed the maximum power conversion efficiency and fill factor of 1.75% and 0.46, respectively. In addition, electrochemical parameters were calculated from electrochemical impedance spectroscopy data under standard simulated sunlight. Transfer resistance at the interfaces and electron life time were decreased as increasing of SnO2 weight ratio, indicated that electron transferring rate was improved.12/2015; 2:108-112. DOI:10.1016/j.promfg.2015.07.019
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ABSTRACT: The properties of waxy rice flour (WRF) and non-waxy rice flour (RF) were modified using an extrusion process with different feeding material moisture contents. WRF was more affected by the thermomechanical stress from extrusion; consequently, it had a lower glass transition temperature but higher water solubility index (WSI) indicating higher molecular degradation than extruded RF. The lower moisture content of the feeding flour caused more severe flour damage (coarser surface of the extruded flour) and lowered relative crystallinity compared to higher moisture content processing. Moreover, low moisture content processing led to complete gelatinization, whereas, partial gelatinization occurred in the higher moisture content extrusion. Consequently, the extruded flours had a lower peak viscosity and gelatinization enthalpy but a higher water absorption index and WSI than native flour. In conclusion, the rice flour type and the moisture content of the extrusion feeding flour affected the physicochemical properties of the extruded flour.Carbohydrate Polymers 12/2014; 114:133–140. DOI:10.1016/j.carbpol.2014.07.074
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