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.     

“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.     

An unsupervised data projection that preserves the cluster structure

In this paper we propose a new unsupervised dimensionality reduction algorithm that looks for a projection that optimally preserves the clustering data structure of the original space. Formally we attempt to find a projection that maximizes the mutual information between data points and clusters in the projected space. In order to compute the mutual information, we neither assume the data are given in terms of distributions nor impose any parametric model on the within-cluster distribution. Instead, we utilize a non-parametric estimation of the average cluster entropies and search for a linear projection and a clustering that maximizes the estimated mutual information between the projected data points and the clusters. The improved performance is demonstrated on both synthetic and real world examples.