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 the method-independent lower bound (MILB) to the variance of attenuation estimation in random reflection

Based on the Cramer-Rao inequality, the MILB is calculated for the problem of estimating the frequency slope of the attenuation coefficient of tissue from random reflections of ultrasonic waves. Under typical signal conditions, this bound for a 1-cm x 1-cm region was found to be about 0.08 db/(MHz-cm), rather close to the clinical requirement of 0.1 dB/(MHz-cm). Comparison to existing methods (including an autoregressive deconvolution method) shows room for further improvement.     

Using previous models to bias structural learning in the hierarchical BOA

Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that explore the space of potential solutions by building and sampling explicit probabilistic models of promising candidate solutions. While the primary goal of applying EDAs is to discover the global optimum or at least its accurate approximation, besides this, any EDA provides us with a sequence of probabilistic models, which in most cases hold a great deal of information about the problem. Although using problem-specific knowledge has been shown to significantly improve performance of EDAs and other evolutionary algorithms, this readily available source of problem-specific information has been practically ignored by the EDA community. This paper takes the first step toward the use of probabilistic models obtained by EDAs to speed up the solution of similar problems in the future. More specifically, we propose two approaches to biasing model building in the hierarchical Bayesian optimization algorithm (hBOA) based on knowledge automatically learned from previous hBOA runs on similar problems. We show that the proposed methods lead to substantial speedups and argue that the methods should work well in other applications that require solving a large number of problems with similar structure.     

A deformable surface model for real-time water drop animation

A water drop behaves differently from a large water body because of its strong viscosity and surface tension under the small scale. Surface tension causes the motion of a water drop to be largely determined by its boundary surface. Meanwhile, viscosity makes the interior of a water drop less relevant to its motion, as the smooth velocity field can be well approximated by an interpolation of the velocity on the boundary. Consequently, we propose a fast deformable surface model to realistically animate water drops and their flowing behaviors on solid surfaces. Our system efficiently simulates water drop motions in a Lagrangian fashion, by reducing 3D fluid dynamics over the whole liquid volume to a deformable surface model. In each time step, the model uses an implicit mean curvature flow operator to produce surface tension effects, a contact angle operator to change droplet shapes on solid surfaces, and a set of mesh connectivity updates to handle topological changes and improve mesh quality over time. Our numerical experiments demonstrate a variety of physically plausible water drop phenomena at a real-time rate, including capillary waves when water drops collide, pinch-off of water jets, and droplets flowing over solid materials. The whole system performs orders-of-magnitude faster than existing simulation approaches that generate comparable water drop effects.     

A system-on-chip development of a neuro-fuzzy embedded agent for ambient-intelligence environments

This paper presents the development of a neuro-fuzzy agent for ambient-intelligence environments. The agent has been implemented as a system-on-chip (SoC) on a reconfigurable device, i.e., a field-programmable gate array. It is a hardware/software (HW/SW) architecture developed around a MicroBlaze processor (SW partition) and a set of parallel intellectual property cores for neuro-fuzzy modeling (HW partition). The SoC is an autonomous electronic device able to perform real-time control of the environment in a personalized and adaptive way, anticipating the desires and needs of its inhabitants. The scheme used to model the intelligent agent is a particular class of an adaptive neuro-fuzzy inference system with piecewise multilinear behavior. The main characteristics of our model are computational efficiency, scalability, and universal approximation capability. Several online experiments have been performed with data obtained in a real ubiquitous computing environment test bed. Results obtained show that the SoC is able to provide high-performance control and adaptation in a life-long mode while retaining the modeling capabilities of similar agent-based approaches implemented on larger computing machines.     

Co-located collaborative visual analytics around a tabletop display

Co-located collaboration can be extremely valuable during complex visual analytics tasks. We present an exploratory study of a system designed to support collaborative visual analysis tasks on a digital tabletop display. Fifteen participant pairs employed Cambiera, a visual analytics system, to solve a problem involving 240 digital documents. Our analysis, supported by observations, system logs, questionnaires, and interview data, explores how pairs approached the problem around the table. We contribute a unique, rich understanding of how users worked together around the table and identify eight types of collaboration styles that can be used to identify how closely people work together while problem solving. We show how the closeness of teams’ collaboration and communication influenced how they performed on the task overall. We further discuss the role of the tabletop for visual analytics tasks and derive design implications for future co-located collaborative tabletop problem solving systems.     

A new mechanism of ultrasonic absorption in aqueous solutions of rigid macromolecules

The temperature- and frequency-dependences of the ultrasonic absorption in lyotropic liquid crystals of rod-like FD virus particles have been measured with the ultrasonic beam being parallel or perpendicular to the rod axis. The experimental results show a strongly anisotropic ultrasonic absorption in the lyotropic liquid crystals, which varies with temperature exactly as the shear viscosity of water. Experimental results are in good agreement with the following model for the absorption process. The authors believe that the absorption arises from differential flow of water between the relatively long and rigid rod-like macromolecules. This mechanism of ultrasonic absorption becomes dominant for frequencies of 1-100 MHz. The validity of this mechanism is, however, not restricted to the special lyotropic crystals discussed here. Instead, this absorption process is expected to be important also for other macromolecular solutions whenever the dissolved macromolecular objects have a sufficiently large linear dimension in the direction parallel to the sound beam.     

Antagonistic effect of some starter cultures on enterobacteriaceae (E. coli)

The ability of Lactobacillus jensenii and Streptococcus 17SB to inbhibit Escherichia coli was demonstrated. The practical application of the inhibition was examined. Possible roles for several factors in the mechanism of inhibition by Lactobacillus jensenii and Streptococcus 17SB are briefly discussed. The effects of pH reached and acids produced by starters on the growth of Escherichia coli are described.     

Prevention of dark-cutting (DFD) beef in penned bulls at the abattoir

There is a large body of evidence indicating that activities associated with regrouping of bulls before slaughter, which leads to physical exhaustion mainly from mounting, are primary factors inducing dark-cutting (DFD) in beef. The aim of this study was to test several methods to control activity when regrouping cannot be avoided. Fifty bulls previously individually tied for at least 16 months were drafted into groups of five animals and released in a pen at the abattoir. After 18 to 22 h they were slaughtered. According to environmental conditions in the pen, the bulls were divided into four groups: Control group (n = 10, no experimentation); Electricity group (n = 10, an electric fence was constructed above the pen so that a mounting bull would receive an electric shock); Darkness group (n = 10, the whole stall was in darkness); and Combination group (n = 20, both treatments, of the electricity and darkness groups were applied). During the first hour of penning the behaviour of the bulls was videorecorded. After slaughter meat quality characteristics were measured. Dark-cutting was found in Control (70%), Electricity (30%) and Darkness (70%) groups, but not in the Combination group (0%). No treatment altered the repertoire of agonistic activity, but under the combined treatments the number of agonistic interactions was significantly lower than in any other group.