Different alphabet indicates the significant difference of variance evaluated by F-test at 95% confidence Ta ble 4. St a nd a r d d ev ia t ion s of P C1 a nd P C 2 fo r the 1-position difference spectra compared with the 3-position difference spectra.
In this study, an intelligent incentive model based on environmental ergonomics in food small and medium-sized enterprises (SMEs) was developed. Environmental ergonomics was defined as the impact of temperature and relative humidity within a certain range on a worker's heart rate during work. Optimum environmental ergonomics are highly required as a basic standard for food SMEs to provide fair incentives. Recommendable parameters from a genetic algorithm and fuzzy inference modeling were used to model customized incentives based on optimum heart rate, workplace temperature and relative humidity before and after working. The research hypothesis stated that industries should optimize their workload and workstation environment prior to customizing incentives. The research objectives were: 1) to recommend optimum environmental ergonomics parameters for customized incentives; 2) to determine the incentives at workstations of SMEs based on optimum environmental ergonomics parameters and fuzzy inference modeling. The optimum values for heart rate, workstation temperature and relative humidity used were based on recommendable values from the genetic algorithm. An inference model was developed to generate decisions whether a worker should receive an incentive based on a calculated index. The results indicated that 84.4% of workers should receive an incentive. The results of this research could be used to promote the concept of ergonomicsbased customized incentives.
In soilless culture, control of nutrient solution is very important for production of the high quality tomato fruits. The control will be efficient by taking the information of internal properties of growing fruits into account.Therefore, nondestructive measurement method for these properties is highly required.Nondestructive near infrared (NIR) methods have already been used effectively in many crops such as mango, apple, peach, however, no studies have been reported on growing tomato fruit. In addition, tomato fruit has a great variation in internal structure that consists of flesh and pulp. It causes ununiformity in texture and chemical compositions within a fruit and hence significantly affects NIR spectra. Therefore, specially assembled NIR instrument is required for accurate nondestructive determination of constituents in the fruit. Three halogen lamps as a light source of the instrument illuminated almost the whole fruit surface from the upper side. Then the spectrum of transmitted light through the bottom of the sample was measured by spectrometer. The performance of this instrument was investigated by developing calibration model for determination of the soluble solids content (SSC) in the whole fruit from the spectrum. This method successfully determined the SSC of tomato fruits with correlation coefficient between predicted and actual values (r) of 0.91, standard error of performance (SEP) of 0.73%, and bias of 0.17%.
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