Design of internal model control based fractional order PID controller

This article presents a design of the internal model control(IMC)based single degree of freedom(SDF) fractional order(FO)PID controller with a desired bandwidth specification for a class of fractional order system(FOS). The drawbacks of the SDF FO-IMC are eliminated with the help of the two-degree of freedom(TDF)FO PID controller. The robust stability and robust performance of the designed controller are analyzed using an example.     

On growth and dispersal of populations

In his unpublished MA thesis of 1921, the young Hotelling invented an ingenious model of population growth and diffusion. The contribution remained widely unknown until Waldo Tobler and Alan Wilson edited it as an article in 1978. Not even then did it trigger off any outburst of contributions. Meanwhile, in 1951, Skellam invented exactly the same model for non-human populations. Unlike in economics, it was a great success in ecology. In a recent contribution Skellam is named Father of Ecological Diffusion and more than a thousand articles on the subject are listed. There were many attempts at solving the equation, but none were quite successful. The Hotelling and Skellam models both assumed a given saturation population that nature could support. In 1985 the present author suggested that an explicit production function be introduced in the Hotelling model, as man produces his own means of subsistence. Moreover it was proposed that diffusion be related to spatial differences in per capita productivity, rather than to those in population density. The present contribution is a rejoinder. It is shown that the stationary solutions to the original Hotelling model are periodic and dip into negative populations, whereas this is avoided by the modified model suggested. It can thus be used to show how agglomerative structures may evolve.     

Ultrasonic imaging of internal vibration of soft tissue under forced vibration

An imaging system that can display both the amplitude and phase maps of internal vibration in soft tissues for forced low-frequency vibration is described. In this method, low-frequency sinusoidal vibration of frequency under several hundred hertz is applied from the surface of the sample and the resulting movement in it is measured from the Doppler frequency shift of the simultaneously transmitted probe ultrasonic waves. Basic experiments are carried out by using 3.0-MHz ultrasonic waves. The two-dimensional maps of the amplitude and phase of internal vibration are shown, and the velocities of vibration are measured for some samples as well as in vivo.     

Training for an agricultural discrimination task

Skeleton weed, centaurea juncea, is a declared weed in Western Australia because it competes with grain crops for nutrients and moisture. When it is found during harvesting, mechanised teams search and eradicate it. In an earlier report of field trials (Hartley et al, 1989) it was reported that search teams' detection rate was poor and since search teams had usually never seen skeleton weeds, visual discrimination learning was to be expected and observed during searches. The present study investigated the nature of this discrimination learning in a laboratory by developing a training programme of colour photographic slides of weeds in stubble. Subjects receiving specific training with feedback on their performance compared with those receiving pseudo-training showed a significant improvement in detections. Subsequently the benefit of the programme was validated in a field trial.     

Visual reasoning about social networks using centrality sensitivity

In this paper, we study the sensitivity of centrality metrics as a key metric of social networks to support visual reasoning. As centrality represents the prestige or importance of a node in a network, its sensitivity represents the importance of the relationship between this and all other nodes in the network. We have derived an analytical solution that extracts the sensitivity as the derivative of centrality with respect to degree for two centrality metrics based on feedback and random walks. We show that these sensitivities are good indicators of the distribution of centrality in the network, and how changes are expected to be propagated if we introduce changes to the network. These metrics also help us simplify a complex network in a way that retains the main structural properties and that results in trustworthy, readable diagrams. Sensitivity is also a key concept for uncertainty analysis of social networks, and we show how our approach may help analysts gain insight on the robustness of key network metrics. Through a number of examples, we illustrate the need for measuring sensitivity, and the impact it has on the visualization of and interaction with social and other scale-free networks.     

Adaptive synthesis of distance fields

We address the computational resource requirements of 3D example-based synthesis with an adaptive synthesis technique that uses a tree-based synthesis map. A signed-distance field (SDF) is determined for the 3D exemplars, and then new models can be synthesized as SDFs by neighborhood matching. Unlike voxel synthesis approach, our input is posed in the real domain to preserve maximum detail. In comparison to straightforward extensions to the existing volume texture synthesis approach, we made several improvements in terms of memory requirements, computation times, and synthesis quality. The inherent parallelism in this method makes it suitable for a multicore CPU. Results show that computation times and memory requirements are very much reduced, and large synthesized scenes exhibit fine details which mimic the exemplars.     

A generalized EM algorithm for 3-D Bayesian reconstruction from Poisson data using Gibbs priors

A generalized expectation-maximization (GEM) algorithm is developed for Bayesian reconstruction, based on locally correlated Markov random-field priors in the form of Gibbs functions and on the Poisson data model. For the M-step of the algorithm, a form of coordinate gradient ascent is derived. The algorithm reduces to the EM maximum-likelihood algorithm as the Markov random-field prior tends towards a uniform distribution. Three different Gibbs function priors are examined. Reconstructions of 3-D images obtained from the Poisson model of single-photon-emission computed tomography are presented.     

Least squares approach in measurement-dependent filtering for selective medical images

An image-processing method called measurement-dependent filtering has been introduced to improve the SNR (signal-to-noise ratio) of selective images produced by various medical imaging systems. The basic algorithm involves the combination of the low-frequency information of the selective image with the high-frequency information of a nonselective image. A spatially variant control function modulates the amount of high frequency to be added at each point. A least-mean-square (LMS) control function formed from two basis images, namely the high-passed versions of the nonselective image (M(b)) and the selective image (S(b)), is introduced. The original algorithm is now viewed as a two-stage filtering method, including the low-pass filtering noise reduction and least squares filtering for the edge restoration. An appropriate linear transformation is used to convert the original basis images M(b) and S(b) into a new pair with orthogonal noise. This allows the implementation of the LMS and control function with practically obtainable a priori knowledge.     

计算机模拟扫描电镜颗粒边缘粗糙度外貌特征

各种石英颗粒表面特征的发育与否,是任何扫描电镜分析重建地质环境的基础,对于在石英颗粒表面获得的许多可见特征来说,虽然已有许多"清单"(Krinsley和Donahue,1968:Cater,1984),但是,专门检测技术的有效性还是一个争论的问题.由这类分析获得的最为重要的物理参数之一是边缘磨蚀,因为圆度值是一种发现于石英砂颗粒的主要形态特征.例如,1984年Goudie和Bull发现两类非洲沉积物之间的主要差异是,在深度风化剖面中总体缺乏边缘磨蚀颗粒,并以此为基础建立了该研究区的斜坡