Position synchronization of multiple motion axes with adaptive coupling control

A new control approach to position synchronization of multiple motion axes is developed, by incorporating cross-coupling technology into adaptive control architecture. The control strategy is to stabilize position tracking of each axis while synchronizing its motion with other axes’ motions so that differential position errors amongst axes converge to zero. The proposed adaptive controller and parameter estimator employ coupling control by feeding back position errors and differential position errors, and have been realized to guarantee asymptotic convergence to zero of both position and synchronization errors. Simulations conducted on a multi-axis motion control system demonstrate the effectiveness of the method.     

Modeling of Temperature–Frequency Correlation Using Combined Principal Component Analysis and Support Vector Regression Technique

A good understanding of environmental effects on structural modal properties is essential for reliable performance of vibration-based damage diagnosis methods. In this paper, a method of combining principal component analysis (PCA) and support vector regression (SVR) technique is proposed for modeling temperature-caused variability of modal frequencies for structures instrumented with long-term monitoring systems. PCA is first applied to extract principal components from the measured temperatures for dimensionality reduction. The predominant feature vectors in conjunction with the measured modal frequencies are then fed into a support vector algorithm to formulate regression models that may take into account thermal inertia effect. The research is focused on proper selection of the hyperparameters to obtain SVR models with good generalization performance. A grid search method with cross validation and a heuristic method are utilized for determining the optimal values of SVR hyperparameters. The proposed method is compared with the method directly using measurement data to train SVR models and the multivariate linear regression (MLR) method through the use of long-term measurement data from a cable-stayed bridge. It is shown that PCA-compressed features make the training and validation of SVR models more efficient in both model accuracy and computational costs, and the formulated SVR model performs much better than the MLR model in generalization performance. When continuously measured data is available, the SVR model formulated taking into account thermal inertia effect can achieve more accurate prediction than that without considering thermal inertia effect.     

An Optimized Content-Aware Authentication Scheme for Streaming JPEG-2000 Images Over Lossy Networks

This paper proposes an optimized content-aware authentication scheme for JPEG-2000 streams over lossy networks, where a received packet is consumed only when it is both decodable and authenticated. In a JPEG-2000 codestream, some packets are more important than others in terms of coding dependency and image quality. This naturally motivates allocating more redundant authentication information for the more important packets in order to maximize their probability of authentication and thereby minimize the distortion at the receiver. Towards this goal, with the awareness of its corresponding image content, we formulate an optimization framework to compute an authentication graph to maximize the expected media quality at the receiver, given specific authentication overhead and knowledge of network loss rate. System analysis and experimental results demonstrate that the proposed scheme achieves our design goal in that the rate-distortion (R-D) curve of the authenticated image is very close to the R-D curve when no authentication is required     

Multichannel Security Protocols

Multichannel security protocols transmit messages over multiple communication channels, taking into account each channel's security properties. Our first intentional use of these protocols goes back to a 1999 article that proposed physical contact for imprinting as opposed to the wireless channel used in subsequent operations. Only later did we understand three key points. First, explicit use of multiple channels in the same protocol can offer significant advantages for both security and usability. Second, explicitly stating the properties of the channel on which each protocol message is transmitted is useful for understanding one's own protocol in greater depth and therefore for addressing subtle vulnerabilities early on. Third, multichannel protocols existed long before we recognized them as such - think of the courier handcuffed to the briefcase carrying the code book that will later protect postal or telegraphic traffic. The paper presents a security protocol that exploit additional transmissions over lower-capacity channels, typically found in ubicomp environments, that offer a different combination of security properties.     

Nonlinear model predictive control with polytopic invariant sets

Ellipsoidal invariant sets have been widely used as target sets in model predictive control (MPC). These sets can be computed by constructing appropriate linear difference inclusions together with additional constraints to ensure that the ellipsoid lies within a given inclusion polytope. The choice of inclusion polytope has a significant effect on the size of the target ellipsoid, but the optimal inclusion polytope cannot in general be computed systematically. This paper shows that use of polytopic invariant sets overcomes this difficulty, allowing larger stabilizable sets without loss of performance. In the interests of online efficiency, consideration is focused on interpolation-based MPC.     

Frequency domain solution to delay-type Nehari problem

This paper generalizes the frequency-domain results on the delay-type Nehari problem in the stable case to the unstable case. The solvability condition of the delay-type Nehari problem is formulated in terms of the nonsingularity of three matrices. The optimal value γ_opt is the maximal γ∈(0,∞) such that one of the three matrices becomes singular. All sub-optimal compensators are parameterized in a transparent structure incorporating a modified Smith predictor.     

EM procedures using mean field-like approximations for Markov model-based image segmentation

Image segmentation using Markov random fields involves parameter estimation in hidden Markov models for which the EM algorithm is widely used. In practice, difficulties arise due to the dependence structure in the models and approximations are required. Using ideas from the mean field approximation principle, we propose a class of EM-like algorithms in which the computation reduces to dealing with systems of independent variables. Within this class, the simulated field algorithm is a new stochastic algorithm which appears to be the most promising for its good performance and speed, on synthetic and real image experiments.     

Determination of vitality from a non-invasive biomedical measurement for use in fingerprint scanners

Fingerprints are the oldest and most widely used biometrics for personal identification. Unfortunately, it is usually possible to deceive automatic fingerprint identification systems by presenting a well-duplicated synthetic or dismembered finger. This paper introduces one method to provide fingerprint vitality authentication in order to solve this problem. Detection of a perspiration pattern over the fingertip skin identifies the vitality of a fingerprint. Mapping the two-dimensional fingerprint images into one-dimensional signals, two ensembles of measures, namely static and dynamic measures, are derived for classification. Static patterns as well as temporal changes in dielectric mosaic structure of the skin, caused by perspiration, demonstrate themselves in these signals. Using these measures, this algorithm quantifies the sweating pattern and makes a final decision about vitality of the fingerprint by a neural network trained by examples.