Fourier transform profilometry employing novel orthogonal elliptic band-pass filtering for accurate 3-D surface reconstruction

The article proposes a novel orthogonal elliptic band-pass filtering methodology in Fourier Transform Profilometry (FTP) for significant improvement of accurate 3-D measurement surface reconstruction with arbitrary object colors. Compared with phase shifting profilometry (PSP), FTP using fringe projection can achieve a general 3-D surface profilometry more efficiently by employing one-shot imaging. However, a challenging problem commonly encountered by FTP using fringe projection is its unreliable extraction of precise spectral information from the spectral domain especially when the spectral domain is complicated to process. Various filtering methods previously proposed in FTP have been proved unsuccessful or nonrobust. Thus, a new band-pass filter is developed from an adaptive orthogonal elliptic region to achieve higher accuracy of 3-D surface reconstruction. A comprehensive theoretical analysis is performed to investigate the physical measurement limits of the proposed method. The experimental results obtained confirm that the measurement accuracy of dimension and sphericity can be greatly enhanced when compared with that achieved by the traditional circular band-pass filter. The proposed method is proved to outperform all the other existing FTP band-pass filtering approaches. The maximum dimensional error measured can be controlled within 1.25% of the overall measuring height with various surface colors. However, it is also verified that the traditional three-step PSP can achieve slightly better measuring repeatability than the proposed method.     

Perspectives on crowdsourcing annotations for natural language processing

Crowdsourcing has emerged as a new method for obtaining annotations for training models for machine learning. While many variants of this process exist, they largely differ in their methods of motivating subjects to contribute and the scale of their applications. To date, there has yet to be a study that helps the practitioner to decide what form an annotation application should take to best reach its objectives within the constraints of a project. To fill this gap, we provide a faceted analysis of crowdsourcing from a practitioner’s perspective, and show how our facets apply to existing published crowdsourced annotation applications. We then summarize how the major crowdsourcing genres fill different parts of this multi-dimensional space, which leads to our recommendations on the potential opportunities crowdsourcing offers to future annotation efforts.     

Red yeast barley reduces plasma glucose levels and activates AMPK phosphorylation in <Emphasis Type="Italic">db/db</Emphasis> mice

Red yeast (Monascus purpureus) fermented over rice has a limited hypoglycemic activity. To enhance its glucose-lowering effect, we fermented red yeast over waxy barley, a hypoglycemic grain with high levels of fibers and β-glucans, and investigated the metabolic effects of red yeast barley (RYB) in high-fat-fed hyperglycemic db/db mice for 6 weeks. The fasting glucose levels were significantly reduced in the RYB group at 6 weeks by 25% (p<0.05), as was the glucose tolerance (−27% of area under the curve in RYB vs. controls, p<0.05). Plasma insulin levels and the expression of PPAR-γ were unaltered, however, the phosphorylation activation of hepatic AMP-activated protein kinase (AMPK) was increased significantly in RYB group compared with controls suggesting that hypoglycemic effect of RYB may be achieved by AMPK-dependent mechanism. RYB may be used as a hypoglycemic functional food modulating cellular AMPK activity.     

An inspection-maintenance model for systems with multiple competing processes

In some applications, the failure rate of the system depends not only on the time, but also upon the status of the system, such as vibration level, efficiency, number of random shocks on the system, etc., which causes degradation. In this paper, we develop a generalized condition-based maintenance model subject to multiple competing failure processes including two degradation processes, and random shocks. An average long-run maintenance cost rate function is derived based on the expressions for the degradation paths & cumulative shock damage, which are measurable. A geometric sequence is employed to develop the inter-inspection sequence. Upon inspection, one needs to decide whether to perform a maintenance, such as preventive or corrective, or to do nothing. The preventive maintenance thresholds for degradation processes & inspection sequences are the decision variables of the proposed model. We also present an algorithm based on the Nelder-Mead downhill simplex method to calculate the optimum policy that minimizes the average long-run maintenance cost rate. Numerical examples are given to illustrate the results using the optimization algorithm.     

Survey of reliability and availability evaluation of complex networks using Monte Carlo techniques

Generally there are four main difficulties in evaluating complex large-scale system reliability, availability and MTBF: the system structure may be very complex; subsystems may follow various failure distributions; subsystems may conform to arbitrary failure and repair distributions for maintained systems; the failure data of subsystems are sometimes not sufficient, reliability test sample sizes tend to be small. It is difficult and often impossible to obtain s-confidence limits of them by classical statistics. Monte Carlo technique combined with Bayes method is a powerful tool to solve this kind of problems. In this survey, the typical existing Monte Carlo reliability, availability and MTBF simulation procedures, variance reduction methods, and random variate generation algorithms are analyzed and summarized. The advantages, drawbacks, accuracy and computer time of Monte Carlo simulation in evaluating reliability, availability and MTBF of a complex network are discussed. Finally, some conclusions are drawn and a general Monte Carlo reliability and MTTF assessment procedure is recommended.     

High-throughput sample preparation for gene expression profiling and in vitro target validation

The demand for high-throughput RNA isolation has been dramatically increasing with wide applications of RNAi, expression profiling, and molecular diagnosis. A comparison of various RNA isolation methods that have been adapted to high-throughput platforms, focusing on consistently high yield and quality of isolated RNA, reduction of cross-contamination, and simplicity and robustness of the protocol is presented. The streamlining of RNA isolation with RNA quantification by qRT-PCR and amplification for microarray analysis is also discussed. In general, a microspheric bead-based approach results in more consistent RNA recovery than glass fiber filter-based RNA isolation method, and RNA can be eluted in a smaller volume. This is because beads can be fully re-suspended in solution to enable more thorough mixing, washing, and elution, whereas the glass fiber matrix is fixed in a filter plate.     

Tank Monitoring: A pAMN Case Study

The introduction of probabilistic behaviour into the B-Method is a recent development. In addition to allowing probabilistic behaviour to be modelled, the relationship between expected values of the machine state can be expressed and verified. This paper explores the application of probabilistic B to a simple case study: tracking the volume of liquid held in a tank by measuring the flow of liquid into it. The flow can change as time progresses, and sensors are used to measure the flow with some degree of accuracy and reliability, modelled as non-deterministic and probabilistic behaviour respectively. At the specification level, the analysis is concerned with the expectation clause in the probabilistic B machine and its consistency with machine operations. At the refinement level, refinement and equivalence laws on probabilistic GSL are used to establish that a particular design of sensors delivers the required level of reliability.     

Reliability analysis of nuclear fail-safe redundancy

In many critical nuclear safety system applications, fault tolerance has been an essential design attribute for achieving high reliability. Generally, operating systems cannot achieve the intended reliability without employing redundancy. Redundant systems, however, require additional resources in terms of both labor and materials. Therefore, the redundancy level needed to achieve fault tolerance must be carefully determined by balancing the reliability and the cost of the systems. In this paper, the optimization problem is formulated and solved for the minimum average total cost of nuclear fail-safe systems. We also determine the optimal system size which minimizes the average total system cost subject to a restricted type I design error. Application and numerical examples are given to illustrate the results.