Lower bound analysis of H ∞ performance achievable via decentralized LTI controllers

This paper is concerned with the decentralized H _∞ controller synthesis problem for discrete‐time LTI systems. Despite of intensive research efforts over the last several decades, this problem is believed to be nonconvex and still outstanding in general. Therefore, most of existing approaches resort to heuristic optimization algorithms that do not allow us to draw any definite conclusion on the quality of the designed controllers. To get around this difficulty, in this paper, we propose convex optimization procedures for computing lower bounds of the H _∞ performance that is achievable via decentralized LTI controllers of any order. In particular, we will show that sharpened lower bounds can be obtained by making good use of structures of the LTI plant typically observed in the decentralized control setting. We illustrate via numerical examples that these lower bounds are indeed useful to ensure the good quality of decentralized controllers designed by a heuristic optimization. Copyright © 2013 John Wiley & Sons, Ltd.     

Exploring Transfer Learning Approaches for Head Pose Classification from Multi-view Surveillance Images

Head pose classification from surveillance images acquired with distant, large field-of-view cameras is difficult as faces are captured at low-resolution and have a blurred appearance. Domain adaptation approaches are useful for transferring knowledge from the training (source) to the test (target) data when they have different attributes, minimizing target data labeling efforts in the process. This paper examines the use of transfer learning for efficient multi-view head pose classification with minimal target training data under three challenging situations: (i) where the range of head poses in the source and target images is different, (ii) where source images capture a stationary person while target images capture a moving person whose facial appearance varies under motion due to changing perspective, scale and (iii) a combination of (i) and (ii). On the whole, the presented methods represent novel transfer learning solutions employed in the context of multi-view head pose classification. We demonstrate that the proposed solutions considerably outperform the state-of-the-art through extensive experimental validation. Finally, the DPOSE dataset compiled for benchmarking head pose classification performance with moving persons, and to aid behavioral understanding applications is presented in this work.     

Efficient Remote Data Possession Checking in Critical Information Infrastructures

Checking data possession in networked information systems such as those related to critical infrastructures (power facilities, airports, data vaults, defense systems, etc.) is a matter of crucial importance. Remote data possession checking protocols permit to check that a remote server can access an uncorrupted file in such a way that the verifier does not need to know beforehand the entire file that is being verified. Unfortunately, current protocols only allow a limited number of successive verifications or are impractical from the computational point of view. In this paper, we present a new remote data possession checking protocol such that: 1) it allows an unlimited number of file integrity verifications; 2) its maximum running time can be chosen at set-up time and traded off against storage at the verifier.     

What Are You Looking at?

In this paper we present a novel mechanism to obtain enhanced gaze estimation for subjects looking at a scene or an image. The system makes use of prior knowledge about the scene (e.g. an image on a computer screen), to define a probability map of the scene the subject is gazing at, in order to find the most probable location. The proposed system helps in correcting the fixations which are erroneously estimated by the gaze estimation device by employing a saliency framework to adjust the resulting gaze point vector. The system is tested on three scenarios: using eye tracking data, enhancing a low accuracy webcam based eye tracker, and using a head pose tracker. The correlation between the subjects in the commercial eye tracking data is improved by an average of 13.91%. The correlation on the low accuracy eye gaze tracker is improved by 59.85%, and for the head pose tracker we obtain an improvement of 10.23%. These results show the potential of the system as a way to enhance and self-calibrate different visual gaze estimation systems.     

Semisupervised learning of classifiers: theory, algorithms, and their application to human-computer interaction

Automatic classification is one of the basic tasks required in any pattern recognition and human computer interaction application. In this paper, we discuss training probabilistic classifiers with labeled and unlabeled data. We provide a new analysis that shows under what conditions unlabeled data can be used in learning to improve classification performance. We also show that, if the conditions are violated, using unlabeled data can be detrimental to classification performance. We discuss the implications of this analysis to a specific type of probabilistic classifiers, Bayesian networks, and propose a new structure learning algorithm that can utilize unlabeled data to improve classification. Finally, we show how the resulting algorithms are successfully employed in two applications related to human-computer interaction and pattern recognition: facial expression recognition and face detection.     

A safety assessment framework of control systems according to international standards

In this paper, we propose an assessment framework for the safety function implemented in a controller according to international standards on safety. Such a function can prevent events where physical values in a control system deviate from the normal operating range, to the fullest extent possible. Therefore, it can decrease the frequency of demand occurrences on externally implemented safety‐related systems and supplement them in risk reduction required by the international standards on safety, such as IEC 61508. In the proposed framework, by evaluating the possibility that the deviations occur because of the true effects of a failure/restoration by using the switching gain for analyzing the fluctuations in transient responses after an unpredictable system switch, we can obtain the demand frequency as an assessment result.     

Behaviour of regenerated polyethylene,recovered from worn out packaging,to artificial ageing and under natural climate conditions

This paper presents the efficiency of styrenated phenol and dian (bisphenol A) stabilizers in high density polyethylene regenerated from worn out packaging samples, by following up the regenerates' behaviour under artificial ageing as well as in natural climate conditions. The efficiency of the stabilizers was assessed by following up the characteristic physical-mechanical modifications and the formation of carbonyl groups in the stabilized, regenerated polyethylene samples, as compared with the primary polyethylene and the unstabilized regenerated samples.