Morphology and intersections of crazes in polystyrene films

Craze network with interconnecting crazes was produced in thin (~60nm) polystyrene films by using a spherical stretching method. For 30% and 45% radial strain, the average mesh size, defined as the square root of average non-crazed areas enclosed by crazes, decreased from about 28m to 4.6 and 2.7m, respectively, as the molecular weight increased from 46 900 to 1 350 000. At a molecular weight of about 10⁶, the interactions between crazes became evident by the split and change of directions at the end of their propagation. Two types of intersection appeared to exist in parallel. The first type showed void formation at the intersections with no apparent fibril displacement effect. The second type showed that the fibrils at the intersection of two perpendicular crazes reoriented to a new direction which seemed to be determined by the relative displacements of the two crazes at the intersections. This observation suggests that the craze fibrils can be displaced and further stretched by a second crazing process.     

A spatially constrained fuzzy hyper-prototype clustering algorithm

We present in this paper a fuzzy clustering algorithm which can handle spatially constraint problems often encountered in pattern recognition. The proposed method is based on the notions of hyperplanes, the fuzzy c-means, and spatial constraints. By adding a spatial regularizer into the fuzzy hyperplane-based objective function, the proposed method can take into account additionally important information of inherently spatial data. Experimental results have demonstrated that the proposed algorithm achieves superior results to some other popular fuzzy clustering models, and has potential for cluster analysis in spatial domain.     

Supervised restoration of degraded medical images using multiple-point geostatistics

Reducing noise in medical images has been an important issue of research and development for medical diagnosis, patient treatment, and validation of biomedical hypotheses. Noise inherently exists in medical and biological images due to the acquisition and transmission in any imaging devices. Being different from image enhancement, the purpose of image restoration is the process of removing noise from a degraded image in order to recover as much as possible its original version. This paper presents a statistically supervised approach for medical image restoration using the concept of multiple-point geostatistics. Experimental results have shown the effectiveness of the proposed technique which has potential as a new methodology for medical and biological image processing.     

Unsupervised active contours driven by density distance and local fitting energy with applications to medical image segmentation

This study presents an efficient variational region-based active contour model for segmenting images without priori knowledge about the object or background. In order to handle intensity inhomogeneities and noise, we propose to integrate into the region-based local intensity model a global density distance inspired by the Bhattacharyya flow. The local term based on local information of segmented image allows the model to deal with bias field artifact, which arises in data acquisition processes. The global term, which is based on the density distance between the probability distribution functions of image intensity inside and outside the active contour, provides information for accurate segmentation, keeps the curve from spilling, and addresses noise in the image. Intensive 2D and 3D experiments on many imaging modalities of medical fields such as computed tomography, magnetic resonance imaging, and ultrasound images demonstrate the effectiveness of the model when dealing with images with blurred object boundary, intensity inhomogeneities, and noise.     

A reinforcement discrete neuro-adaptive control for unknown piezoelectric actuator systems with dominant hysteresis

The theoretical and experimental studies of a reinforcement discrete neuro-adaptive control for unknown piezoelectric actuator systems with dominant hysteresis are presented. Two separate nonlinear gains, together with an unknown linear dynamical system, construct the nonlinear model (NM) of the piezoelectric actuator systems. A nonlinear inverse control (NIC) according to the learned NM is then designed to compensate the hysteretic phenomenon and to track the reference input without the risk of discontinuous response. Because the uncertainties are dynamic, a recurrent neural network (RNN) with residue compensation is employed to model them in a compact subset. Then, a discrete neuro-adaptive sliding-mode control (DNASMC) is designed to enhance the system performance. The stability of the overall system is verified by Lyapunov stability theory. Comparative experiments for various control schemes are also given to confirm the validity of the proposed control.     

A new design method and half-step operation for ultrasonic stepping motors

In this paper, a systematic design method and a new half-step operation are proposed for ultrasonic stepping motors (USMs) which are based on the principle of spatially shifted standing vibrations. With emphasis on the combination of the order of vibration mode, the number of spatial phase shifts, the number of electrodes, and the number of simultaneously excited electrodes, the design equations and constraints are newly derived, hence, proposing the design procedure. The finite-element method and impedance measurement are also employed to investigate the vibration of the stator. By borrowing the control idea of electromagnetic stepping motors, the half-step operation is newly applied to this USM so that the step size can be further halved. An 80-step USM is prototyped. The proposed design method and half-step operation are well supported by experimentation.     

Generalized Linear Quadratic Gaussian Techniques for the Wind Benchmark Problem

This paper presents a comprehensive study of the stage-3 benchmark problem for response control of wind-excited tall buildings based on the linear quadratic gaussian (LQG) approach, and on its generalization, the k-cost-cumulant control method. For control design, the original nodal building model is first transformed into balanced modal space. The Hankel singular values (HSVs) and the power spectral density of the wind disturbances are calculated; and, based on them, a reduced-order model is derived by keeping the first six low-frequency modes. A balanced LQG (BLQG) controller is then determined by adopting the HSVs as a basis to choose the design weights. The main results of the paper are that the BLQG control design is able to come within 5–10% of the performance of the sample LQG controller supplied with the benchmark, but with control actions on the order of one-third less than the sample LQG, and with stability improvement features of a substantial nature over the range of stiffness perturbations specified in the benchmark. Finally, if the low authority BLQG controller is regarded as a one-cost-cumulant design, then with the appropriate use of the second-cost cumulant, the latter methodology is able to demonstrate how higher-authority controllers can give certain improvements in performance, but at the expense of significant investment in control action.     

Four-Dimensional Visualization of Construction Scheduling and Site Utilization

Four-dimensional (4D) models link three-dimensional geometrical models with construction schedule data. The visual link between the schedule and construction site conditions is capable of facilitating decision making during both the planning and construction stages. The emphases of these 4D developments have often been placed at the level of construction components. Practical features assisting site management are at times lacking in the following areas: (1) generation of site usage layouts; (2) estimation of quantities of construction materials; and (3) cost evaluation. In order to pinpoint these deficiencies, the objective of this work is to enable visual study of the effects of job progress on the logistics and resource schedules. This paper presents a 4D visualization model that is intended both to help construction managers plan day-to-day activities more efficiently in a broader and more practical site management context and to thereby add to our knowledge and understanding of the relevance of modern computer graphics to the responsibilities of the construction site manager. A brief site trial of the software is described at the conclusion of the paper.