Automatic stress exaggeration by prosody modification to assist language learners perceive sentence stress

In this paper, we propose a set of automatic stress exaggeration methods that can enlarge the differences between stressed and unstressed syllables. Our stress exaggeration methods can be used in computer-aided language learning systems to assist second language learners perceive stress patterns. The intention of our automatic stress exaggeration methods is to support hyper-pronunciation training which is commonly used in classrooms by teachers. In hyper-pronunciation training, exaggeration is used to help learners increase their awareness of acoustic features and effectively apply these features into their pronunciation. Duration, pitch and intensity have been claimed to be the main acoustic features that are closely related to stress in English language. Thus, four stress exaggeration methods are proposed in this paper: (i) duration-based stress exaggeration, (ii) pitch-based stress exaggeration, (iii) intensity-based stress exaggeration, and (iv) a combined stress exaggeration method that integrates the duration-based, pitch-based and intensity-based exaggeration methods. Our perceptual experimental results show that resynthesised stimuli by our proposed stress exaggerated methods can help learners of English as a Second Language (ESL) better perceive English stress patterns significantly.     

3-D face recognition method based on optimum 3-D image measurement technology

Most face recognition systems employ 2-D color or gray-scale images. However, face recognition based on 2-D images is adversely affected by 3-D movement, variable lighting, and the use of cosmetics. 3-D image measurement technology has the potential to overcome these limitations of face recognition based on 2-D images since it can perform geometric analysis. We propose a method that is capable of recognizing a person from a 3-D facial image obtained using a 3-D shape measurement system by employing a technique that optimizes the intensity-modulation pattern projection. This face recognition method is based on the iterative closest point algorithm. It is robust to changes in reflectivity and color. Since the 3-D facial information can be registered, this method can estimate rotations and translations to compensate for different positions or directions. In order to prove the validity of the proposed technique, a verification experiment was conducted which used 105 sample 3-D images obtained from 15 subjects. It achieved a detection rate of 96% when heads were turned at an angle of 20° or less relative to the camera.     

Centroid Iteration algorithm for image tracking

A simple and elegant tracking algorithm called Centroid Iteration algorithm is proposed. It employs a new Background-Weighted similarity measure which can greatly reduce the influence from the pixels shared by the target template and background on localization. Experiments demonstrated the Background-Weighted measure performs much better than the other similarity measures like Kullback–Leibler divergence, Bhattacharyya coefficient and so on. It has been proved that this measure can compute the similarity value contribution of each pixel in the target candidate, based on which, a new target search method called Centroid Iteration is constructed. The convergence of the method has been demonstrated. Theory analysis and visual experiments both validated the new algorithm.     

Dispersion in Disks

We present three new approximation algorithms with improved constant ratios for selecting n points in n disks such that the minimum pairwise distance among the points is maximized.

1. A very simple O(nlog?n)-time algorithm with ratio 0.511 for disjoint unit disks.
2. An LP-based algorithm with ratio 0.707 for disjoint disks of arbitrary radii that uses a linear number of variables and constraints, and runs in polynomial time.
3. A hybrid algorithm with ratio either 0.4487 or 0.4674 for (not necessarily disjoint) unit disks that uses an algorithm of Cabello in combination with either the simple O(nlog?n)-time algorithm or the LP-based algorithm.

The LP algorithm can be extended for disjoint balls of arbitrary radii in ? ^d , for any (fixed) dimension d, while preserving the features of the planar algorithm. The algorithm introduces a novel technique which combines linear programming and projections for approximating Euclidean distances. The previous best approximation ratio for dispersion in disjoint disks, even when all disks have the same radius, was 1/2. Our results give a positive answer to an open question raised by Cabello, who asked whether the ratio 1/2 could be improved.     

A novel adaptive cooperative location algorithm for wireless sensor networks

To overcome the disadvantages of the location algorithm based on received signal strength indication(RSSI) in the existing wireless sensor networks(WSNs),a novel adaptive cooperative location algorithm is proposed.To tolerate some minor errors in the information of node position,a reference anchor node is employed.On the other hand,Dixon method is used to remove the outliers of RSSI,the standard deviation threshold of RSSI and the learning model are put forward to reduce the ranging error of RSSI and improve the positioning precision effectively.Simulations are run to evaluate the performance of the algorithm.The results show that the proposed algorithm offers more precise location and better stability and robustness.     

Observer‐based Reliable Control for Discrete Time Systems: An Average Dwell Time Approach

This paper deals with the problem of reliable control for discrete time systems with actuator failures. The actuator is assumed to fail occasionally and can recover over a time interval. During the time of suffering failures, the considered closed‐loop system is assumed unstable. Using an average dwell time method and under the condition that the activation time ratio between the system without actuator failures and the system with actuator failures is not less than a specified constant, an observer‐based feedback controller is developed in terms of linear matrix inequalities such that the resulting closed‐loop system is exponentially stable. An example is included to demonstrate the effectiveness of the proposed approach.     

Stability of Impulsive Stochastic Neutral Partial Differential Equations With Infinite Delays

In this paper, we study the existence and asymptotic stability in the pth moment of the mild solutions to impulsive stochastic neutral partial differential equations with infinite delays. Sufficient conditions ensuring the stability of the impulsive stochastic system are established. The results are obtained via the Banach fixed point theorem.     

Intelligent control of doubly‐fed induction generator systems using PIDNNs

An intelligent control for a stand‐alone doubly‐fed induction generator (DFIG) system using a proportional‐integral‐derivative neural network (PIDNN) is proposed in this study. This system can be applied as a stand‐alone power supply system or as the emergency power system when the electricity grid fails for all sub‐synchronous, synchronous, and super‐synchronous conditions. The rotor side converter is controlled using field‐oriented control to produce 3‐phase stator voltages with constant magnitude and frequency at different rotor speeds. Moreover, the grid side converter, which is also controlled using field‐oriented control, is primarily implemented to maintain the magnitude of the DC‐link voltage. Furthermore, the intelligent PIDNN controller is proposed for both the rotor and grid side converters to improve the transient and steady‐state responses of the DFIG system for different operating conditions. Both the network structure and online learning algorithm are introduced in detail. Finally, the feasibility of the proposed control scheme is verified through experimentation. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

A Distributed Workflow Management System with Case Study of Real-life Scientific Applications on Grids

Next-generation scientific applications feature complex workflows comprised of many computing modules with intricate inter-module dependencies. Supporting such scientific workflows in wide-area networks especially Grids and optimizing their performance are crucial to the success of collaborative scientific discovery. We develop a Scientific Workflow Automation and Management Platform (SWAMP), which enables scientists to conveniently assemble, execute, monitor, control, and steer computing workflows in distributed environments via a unified web-based user interface. The SWAMP architecture is built entirely on a seamless composition of web services: the functionalities of its own are provided and its interactions with other tools or systems are enabled through web services for easy access over standard Internet protocols while being independent of different platforms and programming languages. SWAMP also incorporates a class of efficient workflow mapping schemes to achieve optimal end-to-end performance based on rigorous performance modeling and algorithm design. The performance superiority of SWAMP over existing workflow mapping schemes is justified by extensive simulations, and the system efficacy is illustrated by large-scale experiments on real-life scientific workflows for climate modeling through effective system implementation, deployment, and testing on the Open Science Grid.     

Preparation and properties of close-packed composite materials

Monodisperse silica particles of about 0.3m diameter are suspended in methacrylate monomer using a carefully selected dispersant. Many steric dispersants are hydrocarbon chains with a reactive end-group. These are not effective as dispersants for silica in moderately polar solvents, such as esters and the methacrylate monomers. Good dispersion was obtained with a methacrylate polymer terminated by a chlorosilane end group. Settling or centrifugation of these unagglomerated dispersions gives well-packed particle beds. Polymerization of the surrounding monomer produces composite materials with high packing fractions and a high degree of regularity. Moduli and strengths of these composites are reported.