Sirindhorn International Institute of Technology

About: Sirindhorn International Institute of Technology is a based out in . It is known for research contribution in the topics: Supply chain & Combustion. The organization has 1048 authors who have published 1678 publications receiving 30067 citations.

Support Vector Regression for Determination of Minimum Zone

Abstract: Probe-type Coordinate Measuring Machines (CMMs) rely on the measurement of several discrete points to capture the geometry of part features. The sampled points are then fit to verify a specified geometry. The most widely used fitting method, the least squares fit (LSQ), occasionally overestimates the tolerance zone. This could lead to the economical disadvantage of rejecting some good parts and the statistical disadvantage of normal (Gaussian) distribution assumption. Support vector machines (SVMs) represent a relatively new revolutionary approach for determining the approximating function in regression problems. Its upside is that the normal distribution assumption is not required. In this research, support vector regression (SVR), a new data fitting procedure, is introduced as an accurate method for finding the minimum zone straightness and flatness tolerances. Numerical tests are conducted with previously published data and the results are found to be comparable to the published results, illustrating its potential for application in precision data analysis such as used in minimum zone estimation.

A decade of plant-assisted microbial fuel cells: looking back and moving forward

Abstract: Plant microbial fuel cells (PMFCs) have emerged as a renewable source of energy that can produce concurrent bioelectricity and biomass continuously in a clean, sustainable and efficient manner. The...

H2S sensing characteristics of Ni-doped CaCu3Ti4O12 films synthesized by a sol-gel method

Abstract: The problem of detecting the toxic hydrogen sulfide (H2S) gas at part per million levels in air by means of simple solid state gas sensors is relevant to environmental and gas processing industries. In this work, high-performance H2S gas sensors are developed based on nickel-doped calcium copper titanate (Ni-doped CCTO) thin films synthesized by a sol-gel method. From gas-sensing measurements, the response of Ni-doped CCTO sensing films increased substantially with increasing Ni doping level from 1.5 to 7.3 wt%, revealing a catalytic effect of Ni on the surface reactions with adsorbed H2S molecules. In particular, 7.3 wt% Ni-doped CCTO sensors offered a high response of 120 for 10 ppm of H2S at the optimal operating temperature of 250 °C, an order of magnitude higher than that of undoped one. In addition, the response time dropped significantly from ∼80 s to ∼4 s while the recovery time slightly improved as the Ni doping content increased from 0 to 7.3 wt%. Moreover, the Ni-doped CCTO sensors exhibited good reproducibility and high H2S selectivity against ethanol, H2, NO2 and NH3. Therefore, the Ni-doped CCTO sensors are highly promising for sensitive and selective detections of H2S.