Outlier accommodation in moving-horizon state estimation: A risk-averse performance-specified approach

This paper presents a novel state estimation approach for linear dynamic systems when measurements are corrupted by outliers. Since outliers can degrade the performance of state estimation, outlier accommodation is critical. The standard approach combines outlier detection utilizing Neyman-Pearson (NP) type tests with a Kalman filter (KF). This approach ignores all residuals greater than a designer-specified threshold. When measurements with outliers are used (ie, missed detections), both the state estimate and the error covariance matrix become corrupted. This corrupted state and covariance estimate are then the basis for all subsequent outlier decisions. When valid measurements are rejected (ie, false alarms), potentially using the corrupted state estimate and error covariance, measurement information is lost. Either using invalid information or discarding too much valid information can result in divergence of the KF. An alternative approach is moving-horizon (MH) state estimation, which maintains all recent measurement data within a moving window with a time horizon of length L. In MH approaches, the number of measurements available for state estimation is affected by both the number of measurements per time step and the number of time steps L over which measurements are retained. Risk-averse performance-specified (RAPS) state estimation works within an optimization setting to choose a set of measurements that achieves a performance specification with minimum risk of outlier inclusion. This paper derives and formulates the MH-RAPS solution for outlier accommodation. The paper also presents implementation results. The MH-RAPS application uses Global Navigation Satellite Systems measurements to estimate the state of a moving platform using a position, velocity, and acceleration model. In this application, MH-RAPS performance is compared with MH-NP state estimation.     

Effect of iron alloying in evolution of nanostructure and microstructural stability in nickel

Nanocrystalline materials show many interesting properties such as high strength and hardness due to nanosized grains and high density of interfaces. In this context, the present work reports the effect of Fe (iron) addition in Ni (nickel) on nanostructure retention during the annealing of Ni-Fe alloy (with 0, 18.5, 28.5 and 43 wt% Fe) at 450 °C for 16 h. Furthermore, effect of annealing on the deformation mechanism was investigated. The integral breadth method revealed the decrease in grain size with increase in wt% Fe in Ni. The strain rate sensitivity exponent which is a signature of operating deformation mechanism showed a higher value (0.10803) in case of Ni-18.5 wt% Fe during nanoindentation. However, Ni-0 wt% Fe, Ni-28.5 wt% Fe and Ni-43 wt% Fe were characterized by a relatively low strain rate sensitivity exponent (between 0.02069 and 0.10803). Results indicated the presence of Hall-Petch relationship up to 18.5 wt% Fe and inverse Hall-Petch relationship above 18.5 wt% Fe.     

Symmetry building Monte Carlo-based crystal structure prediction

Methods are presented that allow for the automatic increase and preservation of symmetry during global optimization of crystal structures. This systematic building of symmetry allows for its incorporation into structure prediction simulations even when the space group information is not known a priori. It is shown that simulations that build and maintain symmetry converge much more rapidly to ground state crystal structures than when symmetry is ignored, allowing for the treatment of unit cells much larger than would otherwise be possible, especially when beginning from the P1 space group.     

Structural Properties of Boron-Doped Germanium-Tin Alloys Grown by Molecular Beam Epitaxy

Boron-doped Ge_1?x Sn _x alloys with atomic fractions of tin up to x = 0.08 were grown on n-Ge(001) substrates using solid-source molecular beam epitaxy, in order to study their structural properties. The total boron concentration in the alloys was ~ 10¹⁸ cm^?3 as measured by secondary-ion mass spectroscopy, which also indicated low amounts of impurities such as carbon and oxygen. More than 90% of the Sn atoms occupied substitutional lattice sites in the alloy as determined by Rutherford backscattering spectrometry. High-resolution x-ray diffraction showed that the boron-doped Ge_1?x Sn _x alloys were single crystals that were completely strained with low defect densities and coherent interfaces for thickness up to 90 nm, and for Sn composition of 8%. The boron-doped Ge_1?x Sn _x /n-Ge formed p–n junctions with conventional rectifying characteristics, indicating that the boron produced electrically active acceptor states.     

A water coverage extraction approach to track inundation in the Saskatchewan River Delta,Canada

Tracking surface water coverage changes is a complicated task for many regions of the world. It is, however, essential to monitor the associated biological changes and bioproductivity. We present a methodology to track contemporary water coverage changes using optical remote sensing and use it to estimate historical summer water coverage in a large river delta. We used a geographical information system automated routine, based on the modified normalized difference water index, to extract the surface water coverage area (SWCA) from optical satellite data sets using the surface water extraction coverage area tool (SWECAT). It was applied to measure SWCA during drought and flood peaks in the Saskatchewan River Delta in Canada, from Landsat, SPOT and RapidEye images. Landsat results compared favourably with Canadian National Hydro Network (CNHN) GeoBase data, with deviations between SWCA classifications and the base CNHN GeoBase shapefile of ~2%. Difference levels between the extracted SWCA layer from Landsat and the higher resolution commercial satellites (SPOT and RapidEye) were also less than 2%. SWCA was tightly linked to discharge and level measurements from in-channel gauges (r² > 0.70). Using the SWCA versus discharge relationship for the gauge with the longest record, we show that peak summer SWCA has declined by half over the last century, from 13% of our study area to 6%, with likely implications for fish and wildlife production.     

Discrediting in a Message Board Forum: The Effects of Social Support and Attacks on Expertise and Trustworthiness

Given the prevalence of online media today, credibility continues to be a popular subject of empirical research. However, studies examining the effects of discrediting strategies are rare. This issue is significant given the popularity of online media and the ease of such sources to spread misinformation. Therefore, the present study examines the effects of attacking the expertise and trustworthiness of a proponent of a major social issue. Results showed that support as well specific combinations of discrediting attack strategies significantly reduced message board readers' perceptions of the proponent's credibility. In addition, attacks on either the proponent's expertise or trustworthiness resulted in a reduced likelihood of readers taking action with respect to the issue.     

DC-DC电源的设计考虑:在成本、尺寸和性能之间取得平衡

任何电源设计都要对尺寸、成本和性能进行平衡。任何新项目的第一步都是按这三个参数的重要性对其进行排序,作为设计过程的总指导方针。然而,这里面的成本还包括产品的设计成本——其中包括产品销售(COGS)和设计工作的成本。富有经验的设计人员的工作效率更高,因为他们熟悉设计过程、拓扑结构、元器件和潜在的设计困难,还能够判断在什么时候和什么情况下进行额外的设计和定制才值得。     

Applying Genetic Algorithm and Neural Network to the Conjunctive Use of Surface and Subsurface Water

The conjunctive use of surface and subsurface water is one of the most effective ways to increase water supply reliability with minimal cost and environmental impact. This study presents a novel stepwise optimization model for optimizing the conjunctive use of surface and subsurface water resource management. At each time step, the proposed model decomposes the nonlinear conjunctive use problem into a linear surface water allocation sub-problem and a nonlinear groundwater simulation sub-problem. Instead of using a nonlinear algorithm to solve the entire problem, this decomposition approach integrates a linear algorithm with greater computational efficiency. Specifically, this study proposes a hybrid approach consisting of Genetic Algorithm (GA), Artificial Neural Network (ANN), and Linear Programming (LP) to solve the decomposed two-level problem. The top level uses GA to determine the optimal pumping rates and link the lower level sub-problem, while LP determines the optimal surface water allocation, and ANN performs the groundwater simulation. Because the optimization computation requires many groundwater simulations, the ANN instead of traditional numerical simulation greatly reduces the computational burden. The high computing performance of both LP and ANN significantly increase the computational efficiency of entire model. This study examines four case studies to determine the supply efficiencies under different operation models. Unlike the high interaction between climate conditions and surface water resource, groundwater resources are more stable than the surface water resources for water supply. First, results indicate that adding an groundwater system whose supply productivity is just 8.67 % of the entire water requirement with a surface water supply first (SWSF) policy can significantly decrease the shortage index (SI) from 2.93 to 1.54. Second, the proposed model provides a more efficient conjunctive use policy than the SWSF policy, achieving further decrease from 1.54 to 1.13 or 0.79, depending on the groundwater rule curves. Finally, because of the usage of the hybrid framework, GA, LP, and ANN, the computational efficiency of proposed model is higher than other models with a purebred architecture or traditional groundwater numerical simulations. Therefore, the proposed model can be used to solve complicated large field problems. The proposed model is a valuable tool for conjunctive use operation planning.     

Performance evaluation of canine-associated Bacteroidales assays in a multi-laboratory comparison study

The contribution of fecal pollution from dogs in urbanized areas can be significant and is an often underestimated problem. Microbial source tracking methods (MST) utilizing quantitative PCR of dog-associated gene sequences encoding 16S rRNA of Bacteroidales are a useful tool to estimate these contributions. However, data about the performance of available assays are scarce. The results of a multi-laboratory study testing two assays for the determination of dog-associated Bacteroidales (DogBact and BacCan-UCD) on 64 single and mixed fecal source samples created from pooled fecal samples collected in California are presented here. Standardization of qPCR data treatment lowered inter-laboratory variability of sensitivity and specificity results. Both assays exhibited 100% sensitivity. Normalization methods are presented that eliminated random and confirmed non-target responses. The combination of standardized qPCR data treatment, use of normalization via a non-target specific Bacteroidales assay (GenBac3), and application of threshold criteria improved the calculated specificity significantly for both assays. Such measures would reasonably improve MST data interpretation not only for canine-associated assays, but for all qPCR assays used in identifying and monitoring fecal pollution in the environment.     

Multi-laboratory evaluations of the performance of Catellicoccus marimammalium PCR assays developed to target gull fecal sources

Here we report results from a multi-laboratory (n = 11) evaluation of four different PCR methods targeting the 16S rRNA gene of Catellicoccus marimammalium originally developed to detect gull fecal contamination in coastal environments. The methods included a conventional end-point PCR method, a SYBR^® Green qPCR method, and two TaqMan^® qPCR methods. Different techniques for data normalization and analysis were tested. Data analysis methods had a pronounced impact on assay sensitivity and specificity calculations. Across-laboratory standardization of metrics including the lower limit of quantification (LLOQ), target detected but not quantifiable (DNQ), and target not detected (ND) significantly improved results compared to results submitted by individual laboratories prior to definition standardization. The unit of measure used for data normalization also had a pronounced effect on measured assay performance. Data normalization to DNA mass improved quantitative method performance as compared to enterococcus normalization. The MST methods tested here were originally designed for gulls but were found in this study to also detect feces from other birds, particularly feces composited from pigeons. Sequencing efforts showed that some pigeon feces from California contained sequences similar to C. marimammalium found in gull feces. These data suggest that the prevalence, geographic scope, and ecology of C. marimammalium in host birds other than gulls require further investigation. This study represents an important first step in the multi-laboratory assessment of these methods and highlights the need to broaden and standardize additional evaluations, including environmentally relevant target concentrations in ambient waters from diverse geographic regions.