Improving single pixel imaging performance in high noise condition by under-sampling

Single-pixel imaging could be a superior solution for imaging applications where the detector array is very expensive or not even available. Sampling order, sampling ratio, noise and type of transforms affect the quality of the reconstructed image. Here, we compare the performance of single pixel imaging (SPI) with Hadamard transform (HT) and discrete cosine transform (DCT) in the presence of noise. The trade-off between adding image information and adding noise in each coefficient measurement results in an optimum number of measurements for reconstruction image quality. In addition, DCT shows higher image quality with fewer measurements than HT does. We then demonstrate our SPI with optimum sampling strategy for a large set of images and lab experiments and finally put forward a quality control technique, which is corroborated by the practical experiments. Our results suggest a practical approach for SPI to improve the speed and achieve the highest possible image quality.

Is Low-field NMR a Complementary Tool to GC-MS in Quality Control of Essential Oils? A Case Study: Patchouli Essential Oil

High-field NMR is an expensive and important quality control technique. In recent years, cheaper and simpler low-field NMR has become available as a new quality control technique. In this study, 60 MHz 1H-NMR was compared with GC-MS and refractometry for the detection of adulteration of essential oils, taking patchouli essential oil as a test case. Patchouli essential oil is frequently adulterated, even today. In total, 75 genuine patchouli essential oils, 10 commercial patchouli essential oils, 10 other essential oils, 17 adulterants, and 1 patchouli essential oil, spiked at 20% with those adulterants, were measured. Visual inspection of the NMR spectra allowed for easy detection of 14 adulterants, while gurjun and copaiba balsams proved difficult and one adulterant could not be detected. NMR spectra of 10 random essential oils differed not only strongly from patchouli essential oil but also from one another, suggesting that fingerprinting by low-field NMR is not limited to patchouli essential oil. Automated chemometric evaluation of NMR spectra was possible by similarity analysis (Mahalanobis distance) based on the integration from 0.1 – 8.1 ppm in 0.01 ppm increments. Good quality patchouli essential oils were recognised as well as 15 of 17 deliberate adulterations. Visual qualitative inspection by GC-MS allowed for the detection of all volatile adulterants. Nonvolatile adulterants, and all but one volatile adulterant, could be detected by semiquantitation. Different chemometric approaches showed satisfactory results. Similarity analyses were difficult with nonvolatile adulterants. Refractive index measurements could detect only 8 of 17 adulterants. Due to advantages such as simplicity, rapidity, reproducibility, and ability to detect nonvolatile adulterants, 60 MHz 1H-NMR is complimentary to GC-MS for quality control of essential oils.

Simple quality control technique to identify dissolved oxygen diffusion issues with biochemical oxygen demand bottle incubations

Stratified estuaries are home to expanding aquaculture activities whose ecological footprints can be observed through trends in microbial community respiration in the water column. Bottle incubations are widely used to measure water column community respiration in marine and freshwater ecosystems by measuring the flux of dissolved oxygen occurring in the bottle over a period of time. When in situ dissolved oxygen (DO) concentrations are markedly different than DO concentration of the incubation medium the potential for diffusion of oxygen across the bottle opening is great and may be especially pronounced in strongly stratified systems with relatively low rates of pelagic oxygen consumption. We incubated 60 Biochemical Oxygen Demand (BOD) bottles filled with sterilized water with DO concentrations ranging from 2.51 mg O2 L-1 to 10.03 mg O2 L-1 for 24 hours in a temperature controlled water bath. There was a significant relationship when DO flux was set as a function of initial DO (DO Flux = -0.0017x + 0.0085, r2 = 0.72, p < 2.2 e-16). DO fluxes ranged from -0.012 mg O2 L-1 hour-1 to 0.005 mg O2 L-1 hour-1 for bottles incubated with initial DO ranging from 10.03 mg O2 L-1 to 3.31 mg O2 L-1, respectively. These results suggest that diffusion across the ground glass seal of BOD bottles is possible and that extra precaution through parallel diffusion controls should be considered when measuring pelagic respiration using BOD bottle incubations in systems with relatively low or relatively high in situ DO concentrations.

Comparing and diffing XML schemas

Schemas evolve over time, and it is useful to be able to automatically compare versions of a schema in order to provide detailed, accurate documentation to implementers. Automatically “diffing” schemas is also an effective quality control technique, ensuring that inadvertent changes were not made, and that all changes made are backward compatible (if that is a goal). When taking into account the variety of ways of expressing a content model, and the possibility that advanced schema features were used, it is necessary to go beyond simple text diffing or even XML diffing. By first “canonicalizing” schemas to make them easier to compare, and then cataloging the differences between schemas we can answer questions like “Is this schema backward compatible?” and “Is this schema a subset or superset of another schema?”

Modeling, designing and quality control of orthopedic footwear for children and adults

In the manual questions of design, designing and technology of orthopedic footwear for adults and children are considered, types of industrial equipment, the equipment, a quality control technique are given. It is intended for students of the higher educational institutions which are trained in the direction of preparation 260800.62 &#34;Technology, designing of products and materials of light industry&#34;, 29.03.05 &#34;Designing of products light industry&#34;, 29.03.01 &#34;Technology of products of light industry&#34;, 38.03.07 &#34;Merchandizing&#34;, the masters who are trained in the direction 262200.68 &#34;Designing of products of light industry&#34;, 262000.68 &#34;Technology of products of light industry&#34;, 29.04.05 &#34;Designing of products of light industry&#34;, 29.04.01 &#34;Technology of products of light industry&#34;.