‘Anticipatory batch insertion’ to mitigate perceived processing risk

Literature on lot-sizing models with random yields has been traditionally limited to random occurrences that cannot be anticipated in advance; for instance, day-to-day production errors and minor machine repairs. However, in reality, manufacturing processes are subject to other risks that are anticipatory, or non-random, in nature. One example would be yield loss resulting from non-random events such as process, product or material changes. Yield uncertainties of these types are temporary in nature with an impact that decays over time until the manufacturing system fully re-stabilises. One way of reducing the impact of such events is to split the lot and to process a small sub-batch in advance to stabilise the process, thus absorbing the risk associated with the change event. We refer to this approach as ‘anticipatory batch insertion’. This paper presents an exploratory study to analyse the performance of batch insertion under various scenarios related to product sensitivity, risk magnitude and schedule hardness. Results indicate that batch insertion is most advantageous whenever the production schedule is loose, multiple products are sensitive to the risk and the risk magnitude is high.     

Biosynthesis of silver nanoparticles by a Bacillus sp. of marine origin

This study was aimed to explore the nanoparticle synthesizing properties of a silver resistant Bacillus sp. isolated from a marine water sample. The 16SrDNA sequence analysis of the isolate proved it as a Bacillus strain. Very interestingly, the isolate was found to have the ability to form intracellular silver nanoparticles at room temperature within 24 hours. This was confirmed by the UV-Vis absorption analysis which showed a peak at 430 nm corresponding to the plasmon absorbance of silver nanoparticles. Further characterization of the nanoparticles was carried out by transmission electron microscopy (TEM) and scanning electron microscopy (SEM) analysis. The presence of silver nanoparticles with the size less than 100 nm was confirmed. These particles were found to be extremely stable as confirmed by the TEM analysis after three months of purification. So, the current study is the demonstration of an efficient synthesis of stable silver nanoparticles by a marine Bacillus strain.     

Bayesian regularization applied to ultrasound strain imaging

Noise artifacts due to signal decorrelation and reverberation are a considerable problem in ultrasound strain imaging. For block-matching methods, information from neighboring matching blocks has been utilized to regularize the estimated displacements. We apply a recursive Bayesian regularization algorithm developed by Hayton et al. [Artif. Intell., vol. 114, pp. 125-156, 1999] to phase-sensitive ultrasound RF signals to improve displacement estimation. The parameter of regularization is reformulated, and its meaning examined in the context of strain imaging. Tissue-mimicking experimental phantoms and RF data incorporating finite-element models for the tissue deformation and frequency-domain ultrasound simulations are used to compute the optimal parameter with respect to nominal strain and algorithmic iterations. The optimal strain regularization parameter was found to be twice the nominal strain and did not vary significantly with algorithmic iterations. The technique demonstrates superior performance over median filtering in noise reduction at strains 5% and higher for all quantitative experiments performed. For example, the strain SNR was 11 dB higher than that obtained using a median filter at 7% strain. It has to be noted that for applied deformations lower than 1%, since signal decorrelation errors are minimal, using this approach may degrade the displacement image.     

Selection of Accelerometer Location on Bricklayers Using Decision Trees

Abstract: Preliminary investigations on accelerometer‐based activity recognition in construction have shown that it has good potential to be utilized for recognizing categories of work in a construction trade. Selecting the accelerometer locations is an important consideration in activity recognition studies, but currently it is decided primarily on the basis of comfort requirements. This article proposes a methodology for selecting the location of accelerometers using video annotations and decision trees. A video annotation tool is used to track the movement of body segments and decision tree algorithm helps to prioritize the relevant body segments for classifying activities. A two‐phase experimental study was conducted to assess the methodology. In the first phase, video annotation studies were carried out on four bricklayers, and based on decision tree analysis three locations: right lower arm, left lower arm, and waist were selected. In the second phase, an activity recognition study was conducted on another group of bricklayers with accelerometers attached at the selected locations. The results of study show that the location of accelerometer has a significant influence on accuracy and the proposed methodology is effective in selecting accelerometer locations. In the current study only bricklaying activity was considered, however, the methodology is generic and has the potential to be applied to objectively evaluate accelerator placement location for a wide range of structured activities.     

Enhanced superconducting properties of bulk MgB2 prepared by in situ Powder-In-Sealed-Tube method

A systematic study on the superconducting properties of polycrystalline MgB₂ synthesized by in situ Powder-In-Sealed-Tube technique is carried out at different temperatures (750–900 °C). Both XRD and SEM results show well-crystallized MgB₂ grains in all the samples and grain size is found to be increasing with the sintering temperature. Sharp superconducting transitions are observed for all samples, irrespective of sintering temperatures, which implies the high degree phase purity and homogeneity of MgB₂ formed, while J_C(H) plot gives sample dependent critical current density. The samples heat treated at relatively low temperatures show enhanced flux pinning and hence improved J_C(H) performance. The reduced grain size and hence increased density of grain boundary pinning centers of MgB₂ bulks synthesized at low temperature are mainly responsible for the enhanced flux pinning and J_C.