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Nowadays, the world is facing to increasing loss of fossil resources, energy crisis and environmental problems. On the other hand, diesel engines due to wide application in various sectors such as transport, agriculture, industry, etc., are the main sources of emissions and fuel consumption. Accurate measurement of fuel consumption and engine pollution is time-consuming and costly. Hence, the main objective of this study was to develop proper linear regression models of some important performance parameters of ITM285 tractor engine based on engine torque and engine speed. Experiments were carried out in 11 levels of primary engine speed (1063, 1204, 1346, 1488, 1629, 1771, 1818, 1913 and 2054 rpm) by 10 N.m steps of torque from zero (no load) to full load. The measured parameters include fuel consumption mass flow, exhaust temperature, instantaneous engine speed, maximum and mean exhaust opacities. Four different linear regression models were used to estimate the parameters. The results of regression models performance evaluation showed that quadratic model had the highest efficiency and the lowest RMSE for all parameters. The maximum and minimum effects of engine torque were on exhaust temperature and instantaneous engine speed, respectively; while, this result was completely reverse for primary engine speed. The results of regression models evaluation showed a high adaptation between the output of each model and the desired output. Also, the fuel mass flow and exhaust temperature were highly correlated to the maximum and mean exhaust opacity with correlation coefficients of 0.96 and 0.99, respectively.

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In this research, a combined photovoltaic / thermal solar dryer containing phase change materials (PCM) was designed and fabricated for drying mint leaves. The performance of this dryer was evaluated under the climatic conditions of Mashhad city with a longitude of 59.62 and a latitude of 36.26. The components of this dryer mainly include: photovoltaic panel, solar collector, blowers, phase change material chamber containing paraffin wax and drying chamber. Solar dryer and natural drying in shade as two different drying types were used to perform experiments on mint leaves. The initial moisture content of the mint leaves was 80% which reduced to 12%. The required drying time for the combined solar drying and natural drying was 290 minutes and 1560 minutes, respectively. Eight thin layer drying models available in the literature were fitted to the experimental data in which the Two-term model and the Wang and Singh model were the best fit models for natural and combined solar drying respectively. These models have the highest correlation (highest coefficient of determination and least root mean square error and Chi-square) with the experimental moisture ratio among the other models.

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Recent advances in computer technology as well as in signal processing and pattern recognition, provide the possibility of automatic identification of pests, based on their audio signals. In this research a sound reinforced piezoelectric sensor along with a detection circuit based on a database was designed in order to receive audio signals with intensity lower than human hearing limit (zero dB). The confused flour beetle, Triboium confusum was used in this experiment. The signals received from larvae, adult and the combination of these two stages, in wheat grain bulk at three distances of 10, 20 and 30 cm from acoustic sensors were investigated. In each experimental run the characteristics of signals frequency including range, time, amplitude and intensity were extracted. For all three distances the sound produced by the larvae had a peak intensity in the frequency range of 2.4 kHz (for feeding) and the adult insect’s sound had two peaks intensity in the frequency range of 2 kHz (for feeding) and 2.3 kHz (for walking). The differences between the frequency characteristics of sound produced at different stages might provide the possibility of identifying the life stages of the pest, pest distance to the sensor and approximate location of the pest. Based on these findings, the sound sensor and the audio circuit were designed to detect larvae, adult, or both at a distance of 30 cm. Further investigation is continuing to improve the audio system programming and the related circuits for more accurate detection of the pest.