We present algorithms for kinematic manipulation of molecular chains subject to xed bond lengths and bond angles. They are useful for calculating con-formations of a molecule subject to geometric constraints , such as those derived from two-dimensional NMR experiments. Other applications include searching out the full range of conformations available to a molecule such as cyclic conngurations. ...

With the recent technological advancement in submersible systems, the research and development of underwater manipulator robot is highly desirable. This paper focuses on comparing simulation versus real-time manipulator dynamics control, and comparison of intelligent underwater manipulator-robot for effective Ocean-based research, industrial and defense applications. Software package such as MA...

Inverse kinematics (IK) is a nonlinear problem that may have multiple solutions. A modified genetic algorithm (GA) for solving the IK of a serial robotic manipulator is presented. The algorithm is capable of finding multiple solutions of the IK through niching methods. Despite the fact that the number and position of solutions in the search space depends on the position and orientation of the e...

Many statistical problems involve the learning of an importance/effect of a variable for predicting an outcome of interest based on observing a sample of n independent and identically distributed observations on a list of input variables and an outcome. For example, though prediction/machine learning is, in principle, concerned with learning the optimal unknown mapping from input variables to a...

We present an integrated design and marketing approach to facilitate the generation of an optimal robust set of product design alternatives to carry forward to the prototyping stage. The approach considers variability in both (i) engineering design domain, and (ii) customer preferences in marketing domain. In the design domain, the approach evaluates performance and robustness of a design alter...

Gait analysis can provide valuable information on a person's condition and rehabilitation progress. Gait is typically captured using external equipment and/or wearable sensors. These tests are largely constrained to specific controlled environments. In addition, gait analysis often requires experts for calibration, operation and/or to place sensors on volunteers. Alternatively, mobility support...

This paper proposes an Augmented Dickey–Fuller (ADF) coefficient test for detecting the presence of a unit root in autoregressive moving average (ARMA) models of unknown order. Although the limit distribution of the coefficient estimate depends on nuisance parameters, a simple transformation can be applied to eliminate the nuisance parameter asymptotically, providing an ADF coefficient test for...

One of the key challenges in robotic bipedal locomotion is finding gait parameters that optimize a desired performance metric, such as robustness or energy efficiency. Typically, gait optimization requires extensive robot experiments and specific expert knowledge. Instead, we propose to apply data-driven machine learning to automate and speed up the process of gait optimization. In particular, ...

The rapid acquisition of positions by the upcoming Swift satellite will allow the monitoring for X-ray lines in GRB afterglows at much earlier epochs than was previously feasible. We calculate the possible significance levels of iron line detections as a function of source redshift and observing time after the trigger, for the Swift XRT, Chandra ACIS and XMM Epic detectors. For standard burst l...

The aim of this contribution is to discuss approximate Bayesian computation based on the asymptotic theory of modified likelihood roots and log-likelihood ratios. Results on third-order approximations for univariate posterior distributions, also in the presence of nuisance parameters, are reviewed and the computation of asymptotic credible sets for a vector parameter of interest is illustrated....