Bootstrap- and permutation-based inference for the Mann–Whitney effect for right-censored and tied data

The Mann–Whitney effect is an intuitive measure for discriminating two survival distributions. Here we analyse various inference techniques for this parameter in a two-sample survival setting with independent right-censoring, where the survival times are even allowed to be discretely distributed. This allows for ties in the data and requires the introduction of normalized versions of Kaplan–Meier estimators from which adequate point estimates are deduced. Asymptotically exact inference procedures based on standard normal, bootstrap, and permutation quantiles are developed and compared in simulations. Here, the asymptotically robust and—under exchangeable data—even finitely exact permutation procedure turned out to be the best. Finally, all procedures are illustrated using a real data set.     

Multiple circular-harmonic-function correlation filter providing specified response to in-plane rotation

The circular-harmonic-function correlation filter originally proposed by Hsu and Arsenault [Appl. Opt. 21, 4016 (1982)] for in-plane rotation invariance uses only one harmonic, which results in poor discrimination capability of the filter. Various methods to use multiple harmonics were explored previously by different researchers. We present a new method to combine multiple circular harmonics into a single filter that can provide the desired correlation response to in-plane rotation while minimizing the correlation-plane energy. Since multiple harmonics are included, the filter can discriminate well, and since correlation-plane energy is minimized, correlation peaks tend to be sharp. Since the designer can specify the desired in-plane rotation response, a variety of filter behaviors (including complete invariance to input rotations) can be obtained. Underlying theory is discussed, and simulation results are presented.     

Constrained Analytical Trajectory Filter for stabilizing humanoid robot motions

Mimicking human motion with a humanoid robot is essential for allowing humanoid robots to be used in service applications. Simply creating motions without considerations for balance and stability or directly copying motion from a human using motion capture and implementing it on a humanoid robot may not be successful because of the difference in physical properties between the human and the humanoid robot, which may cause instability and make it fall. Using the Zero Moment Point as the stability criteria, this work proposes a Constrained Analytical Trajectory Filter as part of an Analytical Motion Filter, which stabilizes a reference motion that can come from human motion capture data, kinematic synthesis, or animation software. The resulting solutions used in the Constrained Analytical Trajectory Filter provide insight into the complex interactions of motion and stability. The solutions were verified in simulation and with hardware, showing that the analytical filter can be successfully applied for stabilizing reference motions for humanoid robots which may be unstable otherwise.     

Online scheduling on two parallel-batching machines with limited restarts to minimize the makespan

We study online scheduling on two unbounded parallel-batching machines with limited restarts to minimize the makespan. In this system jobs arrive over time and a batch can be restarted if and only if all the jobs in it have never been restarted. To tackle this difficult problem, we make the second-restart assumption whereby we can only interrupt a running batch B at time t if both machines are busy at time t and batch B has a later starting time than the other running batch. For this case, we provide a best online algorithm with a competitive ratio . For the general problem, we show that no online algorithms can have a competitive ratio less than 1.298, leaving a gap from 1.298 to 1.366.     

On scheduling unbounded batch processing machine(s)

The computational complexity of scheduling jobs with released dates on an unbounded batch processing machine to minimize total completion time and on parallel unbounded batch processing machines to minimize total weighted completion time remains open. In this note we show that the first problem is NP-hard with respect to id-encoding, and the second one is strongly NP-hard.     

Linking air quality and watershed models for environmental assessments: Analysis of the effects of model-specific precipitation estimates on calculated water flux

Directly linking air quality and watershed models could provide an effective method for estimating spatially-explicit inputs of atmospheric contaminants to watershed biogeochemical models. However, to adequately link air and watershed models for wet deposition estimates, each model’s temporal and spatial representation of precipitation needs to be consistent. We explore how precipitation implemented within the Community Multi-Scale Air Quality Model (CMAQ) model algorithms, and multiple spatially-explicit precipitation datasets that could be used to improve the CMAQ model deposition estimates, links with the standard precipitation sources used to calibrate watershed models (i.e., rain gage data) via modeled water fluxes. Simulations are run using a grid-based watershed mercury model (GBMM) in two watersheds. Modeled monthly runoff suggests that multiple resolution Parameter-elevations Regressions on Independent Slopes Model (PRISM) and National Multi-sensor Precipitation Analysis Stage IV (NPA) data generate similar monthly runoff estimates, with comparable or greater accuracy when evaluated against stream gage data than that produced by the base rain gage data. However, across longer time periods, simulated water balances using 36 km Pennsylvania State University/National Center for Atmospheric Research mesoscale model (MM5) data are similar to that of base data. The investigation also examines the implications our results, providing suggestions for linking air quality and watershed fate and transport models.     

Disturbance decoupled fault reconstruction using sliding mode observers

This paper investigates and presents conditions that guarantee disturbance decoupled fault reconstruction using sliding mode observers, which are less stringent than those of previous work, and show that disturbance reconstruction is not necessary. An aircraft model validates the ideas proposed in this paper. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Improved sensitivity analysis using a complex variable semi-analytical method

The semi-analytical method (SAM) is a computationally efficient and easy to implement approach often used for the sensitivity analysis of finite element models. However, it is known to exhibit serious inaccuracy for shape sensitivity analysis for structures modeled by beam, frame, plate, or shell elements. In the present paper, we use a semi-analytical approach based on complex variables (SACVM) to compute the sensitivity of finite element models composed of beam and plate elements. The SACVM combines the complex variable method (CVM) with the semi-analytical method (SAM) to obtain the response sensitivity accurately and efficiently. The current approach maintains the computational efficiency of the semi-analytical method but with higher accuracy. In addition, the current approach is insensitive to the choice of step size, a feature that simplifies its use in practical problems. The method is applicable to any structural elements including beam, frame, plate, or shell elements and only requires minor modifications to existing finite element codes.