Unscented Kalman filter based nonlinear model predictive control of a LDPE autoclave reactor

This paper presents a multivariable nonlinear model predictive control (NMPC) scheme for the regulation of a low-density polyethylene (LDPE) autoclave reactor. A detailed mechanistic process model developed previously was used to describe the dynamics of the LDPE reactor and the properties of the polymer product. Closed-loop simulations are used to demonstrate the disturbance rejection and tracking performance of the NMPC algorithm for control of reactor temperature and weight-averaged molecular weight (WAMW). In addition, the effect of parametric uncertainty in the kinetic rate constants of the LDPE reactor model on closed-loop performance is discussed. The unscented Kalman filtering (UKF) algorithm is employed to estimate plant states and disturbances. All control simulations were performed under conditions of noisy process measurements and structural plant–model mismatch. Where appropriate, the performance of the NMPC algorithm is contrasted with that of linear model predictive control (LMPC). It is shown that for this application the closed-loop performance of the UKF based NMPC scheme is very good and is superior to that of the linear predictive controller.     

Express Virtual Channels with Capacitively Driven Global Links

Networks on chip must deliver high bandwidth at low latencies while keeping within a tight power envelope. Using express virtual channels for flow control improves energy-delay throughput by letting packets bypass intermediate routers, but EVCs have key limitations. Nochi (NoC with hybrid interconnect) overcomes these limitations by transporting data payloads and control information on separate planes, optimized for bandwidth and latency respectively.     

Velocity control of a cylindrical rolling robot by shape changing

A rolling robot is developed that possesses an elliptically shaped outer surface with the ability to change shape as it rolls, resulting in a gravity-powered torque imbalance that accelerates or brakes the robot’s motion. Angular position and velocity are measured onboard and used as feedback control to trigger and define shape change actuation. Goal of the control is to direct the robot to follow a given step angular velocity profile. An equation of motion for the rolling robot is derived and solved numerically, and simulations are compared to velocity data from roll trials of the actual robot. Results show that when the robot is given a set of advantageous initial conditions, it is able to accelerate from rest, maintain constant average velocity, and brake its motion in order to follow a desired velocity profile with significant accuracy.     

Interactive multilevel focus+context visualization framework

In this article, we present the construction of an interactive multilevel focus+context visualization framework for the navigation and exploration of large-scale 2D and 3D images. The presented framework utilizes a balanced multiresolution technique supported by a balanced wavelet transform (BWT). It extends the mode of focus+context visualization, where spatially separate magnification of regions of interest (ROIs) is performed, as opposed to in-place magnification. Each resulting visualization scenario resembles a tree structure, where the root constitutes the main context, each non-root internal node plays the dual roles of both focus and context, and each leaf solely represents a focus. Our developed prototype supports interactive manipulation of the visualization hierarchy, such as addition and deletion of ROIs and desired changes in their resolutions at any level of the hierarchy on the fly. We describe the underlying data structure efficiently support such operations. Changes in the spatial locations of query windows defining the ROIs trigger on-demand reconstruction queries. We explain in detail how to efficiently process such reconstruction queries within the hierarchy of details (wavelet coefficients) contained in the BWT in order to ensure real-time feedback. As the BWT need only be constructed once in a preprocessing phase on the server-side and robust on-demand reconstruction queries require minimal data communication overhead, our presented framework is a suitable candidate for efficient web-based visualization of complex large-scale imagery. We also discuss the performance characteristics of our proposed framework from various aspects, such as time and space complexities and achieved frame rates.     

“This is the size of one meter”: Children’s bodily-material collaboration

In CSCL studies, language is often foregrounded as the primary resource for engaging in collaborative learning, while the body is more often positioned as a secondary resource. There is, however, a growing interest in the body as a resource in learning and collaboration in and outside CSCL. In this paper, we present, analyse, and discuss how two nine-year-old children collaborate through gesturing and moving their bodies around a touchscreen. The pair is working with the concept of scale and area measurement and are in midst of copying their rooms from paper to touchscreen. During this process, the pair engages in a discussion regarding the size of one meter through language, gestures and manipulation of the material resources. The analysis shows two distinct ways of understanding the length of one meter, which primarily are visible through the children’s gestures and bodily movements. In the analysis we show how the children dynamically produce body-material resources for communicative and illustrative purposes; moreover, they use body-material resources as a cognitive tool and as a way of shepherding each other. The study forms part of a body of studies analysing and theorizing the body in education, learning, and interaction. We discuss the wider impact of our findings and argue how they may challenge and improve studies relying mainly on a coding and counting approach or automated capture of e.g. gestures. In addition, we provide a detailed multimodal representation of the subtle bodily-material resources, which we argue is a modest contribution to a catalogue of ways of representing and making bodily-material resources visible in CSCL research.     

On The Modeling of Twin Rotor MIMO System Using Chirp Inputs as Test Signals

This paper addresses the modeling problem for the twin rotor multi input multi output system. To develop experimental data, this popular commercial laboratory model of a helicopter from Feedback Instruments Ltd is excited with band limited chirp inputs. The conclusions drawn in this paper lead to four significant achievements: 1) derivation of a linear nominal model for Twin Rotor MIMO System, TRMS in short, from its equivalent nonlinear mathematical representation; 2) dynamic modeling of TRMS; 3) determination of non‐minimum phase dynamics; and 4) determination of linear operating region. The work considers systematic study of the system dynamics of TRMS and analytical treatment of its identified data leading to derivation of the RHP zero dynamics followed by pictorial illustrations indicating resonant modes associated with the plant. The method used in the present paper can be essentially used in modeling of 2 × 2 plants exhibiting non‐minimum phase dynamics and model uncertainties.     

SEBS elastomers for fabrication of microfluidic devices with reduced drug absorption by injection molding and extrusion

The majority of microfluidic devices used for cell culture, including Organ-on-a-Chips (Organ Chips), are fabricated using polydimethylsiloxane (PDMS) polymer because it is flexible, optically clear, and easy to mold. However, PDMS possesses significant challenges for high volume manufacturing and its tendency to absorb small hydrophobic compounds limits its usefulness as a material in devices used for drug evaluation studies. Here, we demonstrate that a subset of optically clear, elastomeric, styrenic block copolymers based on styrene-ethylene-butylene-styrene exhibit reduced absorption of small hydrophobic molecules and drug compounds compared to PDMS and that they can be fabricated into microfluidic devices with fine features and the flexibility required for Organ Chips using mass production techniques of injection molding and extrusion.     

Light scattering from anisotropic, randomly rough, perfectly conducting surfaces

An approach is introduced for performing rigorous numerical simulations of electromagnetic wave scattering from randomly rough, perfectly conducting surfaces. It is based on a surface integral technique, and consists of determining the unknown electric surface current densities from which the electromagnetic field everywhere can be determined. The method is used to study the scattering of a p-polarized beam from an anisotropic Gaussian, randomly rough, perfectly conducting surface. It is demonstrated that the surface anisotropy gives rise to interesting and pronounced signatures in the angular intensity distribution of the scattered light. The origins of these features are discussed.     

Fovea center detection based on the retina anatomy and mathematical morphology

In this work, we present a new fovea center detection method for color eye fundus images. This method is based on known anatomical constraints on the relative locations of retina structures, and mathematical morphology. The detection of this anatomical feature is a prerequisite for the computer aided diagnosis of several retinal diseases, such as Diabetic Macular Edema. The proposed method is adaptive to local illumination changes, and it is robust to local disturbances introduced by pathologies in digital color eye fundus images (e.g. exudates). Our experimental results using the DRIVE image database indicate that our method is able to detect the fovea center in 37 out of 37 images (i.e. with a success rate of 100%). Using the DIARETDB1 database, our method was able to detect the fovea center in 92.13% of all tested cases (i.e. in 82 out of 89 images). These results indicate that our approach potentially can achieve a better performance than comparable methods proposed in the literature.     

Behavioral detection of malware: from a survey towards an established taxonomy

Behavioral detection differs from appearance detection in that it identifies the actions performed by the malware rather than syntactic markers. Identifying these malicious actions and interpreting their final purpose is a complex reasoning process. This paper draws up a survey of the different reasoning techniques deployed among the behavioral detectors. These detectors have been classified according to a new taxonomy introduced inside the paper. Strongly inspired from the domain of program testing, this taxonomy divides the behavioral detectors into two main families: simulation-based and formal detectors. Inside these families, ramifications are then derived according to the data collection mechanisms the data interpretation, the adopted model and its generation, and the decision support.